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Lead Data Engineer

What are we looking for

real solver?

Solver? Absolutely. But not the usual kind. We're searching for the architects of the audacious & the pioneers of the possible. If you're the type to dismantle assumptions, re-engineer ‘best practices,’ and build solutions that make the future possible NOW, then you're speaking our language.

Your Responsibilities

What you will wake up to solve.

• Lead Technical Design & Data Architecture: Architect and lead the end-to-end development of scalable, cloud-native data platforms. You’ll guide the squad on critical architectural decisions—choosing between Batch vs. Streaming or ETL vs. ELT—while remaining 100% hands-on, contributing high-quality, production-grade code.
• Build High-Velocity Data Pipelines: Drive the implementation of robust data transports and ingestion frameworks using Python, SQL, and Spark. You will build integration layers that connect heterogeneous sources (SaaS, RDBMS, NoSQL) into unified, high-availability environments like BigQuery, Snowflake, or Redshift.
• Mentor & Elevate the Squad: Foster a culture of technical excellence by mentoring and inspiring a team of data analysts and engineers. Lead deep-dive code reviews, promote best-practice data modeling (Star/Snowflake schema), and ensure the squad adopts modern engineering standards like CI/CD for data.
• Drive AI-Ready Data Strategy: Be the expert in designing data foundations optimized for AI and Machine Learning. You will champion the use of GCP (Dataflow, Pub/Sub, BigQuery) and AWS (Lambda, Glue, EMR) to create "clean room" environments that fuel advanced analytics and generative AI models.
• Partner with Clients as a Technical DRI: Act as the Directly Responsible Individual for client success. Translate ambiguous business questions into elegant data services, manage project deliverables using Agile methodologies, and ensure that the data provided is accurate, consistent, and mission-critical.
• Troubleshoot & Optimize for Scale: Own the reliability of the reporting layer. You will proactively monitor pipelines, troubleshoot complex transformation bottlenecks, and propose ways to improve platform performance and cost-efficiency.
• Innovate and Build Reusable IP: Spearhead the creation of reusable data frameworks, custom operators, and transformation libraries that accelerate future projects and establish Searce’s unique technical advantage in the market.

Welcome to Searce

The AI-Native tech consultancy that's rewriting the rules.

Searce is an AI-native, engineering-led, modern tech consultancy that empowers clients to futurify their business by delivering intelligent, impactful, real business outcomes. Searce solvers co-innovate with clients as their trusted transformational partners ensuring sustained competitive advantage. Searce clients realize smarter, faster, better business outcomes delivered by AI-native Searce solver squads. 

Functional Skills 

the solver personas.

• The Data Architect: This persona deconstructs ambiguous business goals into scalable, elegant data blueprints. They don't just move data; they design the foundation—from schema design to partitioning strategies—that allows data scientists and analysts to thrive, foreseeing technical bottlenecks and making pragmatic trade-offs.
• The Player-Coach: As a hands-on leader, this persona leads from the front by writing exemplary, production-grade SQL and Python while simultaneously mentoring and elevating the skills of the squad. Their success is measured by the team's ability to deliver high-quality, maintainable code and their growth as engineers.
• The Pragmatic Innovator: This individual balances a passion for modern data tech (like Generative AI and Real-time Streaming) with a sharp focus on business outcomes. They champion new tools where they add real value but are disciplined enough to choose stable, cost-effective solutions to meet deadlines and deliver robust products.
• The Client-Facing Technologist: This persona acts as the crucial technical bridge between the data squad and the client. They build trust by listening actively, explaining complex data concepts (like data latency or idempotency) in simple terms, and demonstrating how engineering decisions align with the client’s strategic goals.
• The Quality Craftsman: This individual possesses an unwavering commitment to data integrity and treats data engineering as a craft. They are the guardian of the reporting layer, advocating for robust testing, data validation frameworks, and clean, modular code to ensure the long-term reliability of the data platform.

Experience & Relevance 

• Engineering Depth: 7-10 years of professional experience in end-to-end data product development. You have a portfolio that proves your ability to build complex, high-velocity pipelines for both Batch and Streaming workloads.
• Cloud-Native Fluency: Deep, hands-on experience designing and deploying scalable data solutions on at least one major cloud platform (AWS, GCP, or Azure). You are comfortable navigating the nuances of EMR, BigQuery, or Synapse at scale.
• AI-Native Workflow: You don’t just build for AI; you build with AI. You must be proficient in using AI coding assistants (e.g., GitHub Copilot) to accelerate your delivery and have a track record of building the data foundations required for Generative AI.
• Architectural Portfolio: Evidence of leading 2-3 large-scale transformations—including platform migrations, data lakehouse builds, or real-time analytics architectures.
• Client-Facing Acumen: You have direct experience in a consultative, client-facing role. You can confidently translate a CEO’s business vision into a Lead Engineer’s technical specification without losing anything in translation.

Join the ‘real solvers’

ready to futurify?

If you are excited by the possibilities of what an AI-native engineering-led, modern tech consultancy can do to futurify businesses, apply here and experience the ‘Art of the possible’. Don’t Just Send a Resume. Send a Statement.

Director - Data engineering

What are we looking for

real solver?

Solver? Absolutely. But not the usual kind. We're searching for the architects of the audacious & the pioneers of the possible. If you're the type to dismantle assumptions, re-engineer ‘best practices,’ and build solutions that make the future possible NOW, then you're speaking our language.

Your Responsibilities

what you will wake up to solve.

1. Delivery & Tactical Rigor

• Methodology Implementation: Implement and manage a unified, 'DataOps-First' methodology for data engineering delivery (ETL/ELT pipelines, Data Modeling, MLOps, Data Governance) within assigned business units. This ensures predictable outcomes and trusted data integrity by reducing architecture variability at the project level.
• Operational Stewardship: Drive initiatives to optimize team utilization and enhance operational efficiency within the practice. You manage the commercial success of your squads, ensuring data delivery models (from migration to modern data stack implementation) are executed profitably, scalably, and cost-effectively.
• Execution & Technical Resolution
• Technical Escalation: Serve as the primary escalation point for delivery issues, personally leading the resolution of complex data integration bottlenecks and pipeline failures to protect client timelines and data reliability standards.
• Quality Enforcement
• Quality Oversight: Execute and monitor technical data quality standards, ensuring engineering teams adhere to strict policies regarding data lineage, automated quality checks (observability), security/privacy compliance (GDPR/CCPA/PII), and active catalog management.

2. Strategic Growth & Practice Scaling

• Talent & Scaling Execution: Execute the strategy for data engineering talent acquisition and development within your business units. Implement objective metrics to assess and grow the 'Data-Native' DNA of your teams, ensuring squads are consistently equipped to handle petabyte-scale environments and high-impact delivery.
• Offerings Alignment: Drive the adoption of standardized regional offerings (e.g., Modern Data Platform, Data Mesh, Lakehouse Implementation). Ensure your teams leverage the profitable frameworks defined by the practice to accelerate time-to-insight and eliminate architectural fragmentation in client environments.
• Innovation & IP Development: Lead the practical integration of Vector Databases and LLM-ready architectures into project delivery. Champion the hands-on development of IP and reusable accelerators (e.g., automated ingestion engines) that improve delivery speed and enhance data availability across your portfolio.

3. Leadership & Unit Management

• Unit Leadership: Directly lead, mentor, and manage the Engineering Managers and Lead Architects within your business unit. Hold your teams accountable for project-level operational consistency, technical talent development, and strict adherence to the practice's data governance standards.
• Stakeholder Communication: Clearly articulate the business unit’s operational performance, technical quality metrics, and delivery progress to the C-suite Stakeholders and regional client leadership, bridging the gap between technical execution and business value.
• Ecosystem Alignment: Maintain strong technical relationships with key partner contacts (Snowflake, Databricks, AWS/GCP). Align team delivery capabilities with current product roadmaps and ensure squad-level participation in training, certifications, and partner-led enablement opportunities.

Welcome to Searce

The ‘process-first’, AI-native modern tech consultancy that's rewriting the rules.

We don’t do traditional.

As an engineering-led consultancy, we are dedicated to relentlessly improving the real business outcomes. Our solvers co-innovate with clients to futurify operations and make processes smarter, faster & better.

Functional Skills

1. Delivery Management & Operational Excellence

• Methodology Execution: Expert capability in implementing and enforcing a unified delivery methodology (DataOps, Agile, Mesh Principles) within specific business units. Proven track record of auditing squad-level adherence to ensure consistency across the project lifecycle.
• Operational Performance: High proficiency in managing day-to-day operational metrics, including squad utilization, resource forecasting, and productivity tracking. Skilled at optimizing team performance to meet profitability and efficiency targets.
• SOW & Risk Mitigation: Proven experience in operationalizing Statement of Work (SOW) requirements and identifying technical delivery risks early. Expert at mitigating scope creep and data-specific bottlenecks (e.g., latency, ingestion gaps) before they impact client outcomes.
• Technical Escalation Leadership: Demonstrated ability to lead "war room" efforts to resolve complex pipeline failures or data integrity issues. Skilled at providing clear, rapid remediation plans and communicating technical status directly to regional stakeholders.

2. Architectural Implementation & Technical Oversight

• Modern Stack Proficiency: Deep, hands-on expertise in implementing Cloud-Native architectures (Lakehouse, Data Mesh, MPP) on Snowflake, Databricks, or hyperscalers. Ability to conduct deep-dive architectural reviews and course-correct design decisions at the squad level to ensure scalability.
• Operationalizing Governance: Proven experience in embedding data quality and observability (completeness, freshness, accuracy) directly into the CI/CD pipeline. Responsible for technical enforcement of regulatory compliance (GDPR/PII) and maintaining the integrity of data catalogs across active projects.
• Applied Domain Expertise: Practical experience leading the delivery of high-growth solutions, specifically Generative AI infrastructure (RAG, Vector DBs), Real-Time Streaming, and large-scale platform migrations with a focus on zero-downtime execution.
• DataOps & Engineering Standards: Expert-level mastery of DataOps, including the setup and management of orchestration frameworks (Airflow, Dagster) and Infrastructure as Code (IaC). You ensure that automation is a baseline requirement, not an afterthought, for all delivery teams.

3. Unit Management & Commercial Execution

• Unit & Team Management: Proven success in leading and mentoring Engineering Managers and Lead Architects. Responsible for the operational metrics, technical output, and career development of the business unit's talent pool.
• Offerings Implementation & Scoping: Expertise in translating service offerings (e.g., Data Maturity Assessments, Lakehouse Builds) into accurate project scopes, technical estimates, and resource plans to ensure delivery is both profitable and competitive.
• Talent Growth & Mentorship: Functional ability to implement growth frameworks for data engineering roles. Focus on hands-on coaching and scaling high-performance technical talent to meet the demands of complex, petabyte-scale environments.
• Partner Enablement: Functional competence in managing regional technical relationships with major partners (Snowflake, Databricks, GCP/AWS). Drives squad-level certifications, joint technical enablement, and alignment with partner product roadmaps.

Tech Superpowers

• Modern Data Architect – Reimagines business with the Modern Data Stack (MDS) to deliver data mesh implementations, insights, & real value to clients.
• End-to-End Ecosystem Thinker – Builds modular, reusable data products across ingestion, transformation (ETL/ELT), governance, and consumption layers.
• Distributed Compute Savant – Crafts resilient, high-throughput architectures that survive petabyte-scale volume and data skew without breaking the bank.
• Governance & Integrity Guardian – Embeds data quality, complete lineage, and privacy-by-design (GDPR/PII) into every table, view, and pipeline.
• AI-Ready Orchestrator – Engineers pipelines that bridge structured data with Unstructured/Vector stores, powering RAG models and Generative AI workflows.
• Product-Minded Strategist – Balances architectural purity with time-to-insight; treats every dataset as a measurable "Data Product" with clear ROI.
• Pragmatic Stack Curator – Chooses the simplest tools that compound reliability; fluent in SQL, Python, Spark, dbt, and Cloud Warehouses.
• Builder @ Heart – Writes, reviews, and optimizes queries daily; proves architectures with cost-performance benchmarks, not slideware. Business-first, data-second, outcome focused technology leader.

Experience & Relevance

• Executive Experience: Minimum 10+ years of progressive experience in data engineering and analytics, with at least 3 years in a Senior Manager or Director -level role managing multiple technical teams and owning significant operational and efficiency metrics for a large data service line.
• Delivery Standardization: Demonstrated success in defining and implementing globally consistent, repeatable delivery methodologies (DataOps/Agile Data Warehousing) across diverse teams.
• Architectural Depth: Must retain deep, current expertise in Modern Data Stack architectures (Lakehouse, MPP, Mesh) and maintain the ability to personally validate high-level architectural and data pipeline design decisions.
• Operational Leadership: Proven expertise in managing and scaling large professional services organizations, demonstrated ability to optimize utilization, resource allocation, and operational expense.
• Domain Expertise: Strong background in Enterprise Data Platforms, Applied AI/ML, Generative AI integration, or large-scale Cloud Data Migration.
• Communication: Exceptional executive-level presentation and negotiation skills, particularly in communicating complex operational, data quality, and governance metrics to C-level stakeholders.

Join the ‘real solvers’

ready to futurify?

If you are excited by the possibilities of what an AI-native engineering-led, modern tech consultancy can do to futurify businesses, apply here and experience the ‘Art of the possible’. Don’t Just Send a Resume. Send a Statement.

Solutions Architect - Data Engineering

Modern tech solutions advisory & 'futurify' consulting as a Searce lead fds (‘forward deployed solver’) architecting scalable data platforms and robust data engineering solutions that power intelligent insights and fuel AI innovation.

If you’re a tech-savvy, consultative seller with the brain of a strategist, the heart of a builder, and the charisma of a storyteller — we’ve got a seat for you at the front of the table.

You're not a sales lead. You're the transformation driver.

What are we looking for

real solver?

Solver? Absolutely. But not the usual kind. We're searching for the architects of the audacious & the pioneers of the possible. If you're the type to dismantle assumptions, re-engineer ‘best practices,’ and build solutions that make the future possible NOW, then you're speaking our language.

• Improver. Solver. Futurist.
• Great sense of humor.
• ‘Possible. It is.’ Mindset.
• Compassionate collaborator. Bold experimenter. Tireless iterator.
• Natural creativity that doesn’t just challenge the norm, but solves to design what’s better.
• Thinks in systems. Solves at scale.

This Isn’t for Everyone. But if you’re the kind who questions why things are done a certain way— and then identifies 3 better ways to do it — we’d love to chat with you.

Your Responsibilities

what you will wake up to solve.

You are not just a Solutions Architect; you are a futurifier of our data universe and the primary enabler of our AI ambitions. With a deep-seated passion for data engineering, you will architect and build the foundational data infrastructure that powers the customers entire data intelligence ecosystem.

As the Directly Responsible Individual (DRI) for our enterprise-grade data platforms, you own the outcome, end-to-end. You are the definitive solver for our customer's most complex data challenges, leveraging a powerful tech stack including Snowflake, Databricks, etc. and core GCP & AWS services (BigQuery, Spanner, Airflow, Kafka). This is a hands-on-keys role where you won't just design solutions—you'll build them, break them, and perfect them.

• Solution Design & Pre-sales Excellence:Collaborate with cross-functional teams, including sales, engineering, and operations, to ensure successful project delivery.
• Design Core Data Engineering: Master data modeling, architecting high-performance data ingestion pipelines and ensuring data quality and governance throughout the data lifecycle.
• Enable Cloud & AI: Design and implement solutions utilizing core GCP data services, building foundational data platforms that efficiently support advanced analytics and AI/ML initiatives.
• Optimize Performance & Cost: Continuously optimize data architectures and implementations for performance, efficiency, and cost-effectiveness within the cloud environment.
• Bridge Business & Tech: Translate complex business requirements into clear technical designs, providing technical leadership and guidance to data engineering teams.
• Stay Ahead of the Curve: Continuously research and evaluate new data technologies, architectural patterns, and industry trends to keep our data platforms at the cutting edge.

Functional Skills:

• Enterprise Data Architecture Design: Expert ability to design holistic, scalable, and resilient data architectures for complex enterprise environments.
• Cloud Data Platform Strategy: Proven capability to strategize, design, and implement cloud-native data platforms.
• Pre-Sales & Technical Storyteller: Crafts compelling, client-ready proposals, architectural decks, and technical demonstrations. Doesn't just present; shapes the strategic technical narrative behind every proposed solution.
• Advanced Data Modelling: Mastery in designing various data models for analytical, operational, and transactional use cases.
• Data Ingestion & Pipeline Orchestration: Strong expertise in designing and optimizing robust data ingestion and transformation pipelines.
• Stakeholder Communication: Exceptional skills in articulating complex technical concepts and architectural decisions to both technical and non-technical stakeholders.
• Performance & Cost Optimization: Adept at optimizing data solutions for performance, efficiency, and cost within a cloud environment.

Tech Superpowers:

• Cloud Data Mastery: You're a wizard at leveraging public cloud data services, with deep expertise in GCP (BigQuery, Spanner, etc.) and expert proficiency in modern data warehouse solutions like Snowflake.
• Data Engineering Core: Highly skilled in designing, implementing, and managing data workflows using tools like Apache Airflow and Apache Kafka. You're also an authority on advanced data modeling and ETL/ELT patterns.
• AI/ML Data Foundation: You instinctively design data pipelines and structures that efficiently feed and empower Machine Learning and Artificial Intelligence applications.
• Programming for Data: You have a strong command over key programming languages (Python, SQL) for scripting, automation, and building data processing applications.

Experience & Relevance:

• Architectural Leadership (8+ Years): You bring extensive experience (7+ years) specifically in a Solutions Architect role, focused on data engineering and platform building.
• Cloud Data Expertise: You have a proven track record of designing and implementing production-grade data solutions leveraging major public cloud platforms, with significant experience in Google Cloud Platform (GCP).
• Data Warehousing & Data Platform: Demonstrated hands-on experience in the end-to-end design, implementation, and optimization of modern data warehouses and comprehensive data platforms.
• Databricks & BigQuery Mastery: You possess significant practical experience with Databricks as a core data warehouse and GCP BigQuery for analytical workloads.
• Data Ingestion & Orchestration: Proven experience designing and implementing complex data ingestion pipelines and workflow orchestration using tools like Airflow and real-time streaming technologies like Kafka.
• AI/ML Data Enablement: Experience in building data foundations specifically geared towards supporting Machine Learning and Artificial Intelligence initiatives.

Join the ‘real solvers’

ready to futurify?

If you are excited by the possibilities of what an AI-native engineering-led, modern tech consultancy can do to futurify businesses, apply here and experience the ‘Art of the possible’.

Don’t Just Send a Resume. Send a Statement.

So, If you are passionate about tech, future & what you read above (we really are!), apply here to experience the ‘Art of Possible’

What You’ll Do:

We are looking for a Staff Operations Engineer based in Pune, India who can master both DeepIntent’s data architectures and pharma research and analytics methodologies to make significant contributions to how health media is analyzed by our clients. This role requires an Engineer who not only understands DBA functions but also how they impact research objectives and can work with researchers and data scientists to achieve impactful results.  

This role will be in the Engineering Operations team and will require integration and partnership with the Engineering Organization. The ideal candidate is a self-starter who is inquisitive who is not afraid to take on and learn from challenges and will constantly seek to improve the facets of the business they manage. The ideal candidate will also need to demonstrate the ability to collaborate and partner with others.  

• Serve as the Engineering interface between Analytics and Engineering teams.
• Develop and standardize all interface points for analysts to retrieve and analyze data with a focus on research methodologies and data-based decision-making.
• Optimize queries and data access efficiencies, serve as an expert in how to most efficiently attain desired data points.
• Build “mastered” versions of the data for Analytics-specific querying use cases.
• Establish a formal data practice for the Analytics practice in conjunction with the rest of DeepIntent.
• Interpret analytics methodology requirements and apply them to data architecture to create standardized queries and operations for use by analytics teams.
• Implement DataOps practices.
• Master existing and new Data Pipelines and develop appropriate queries to meet analytics-specific objectives.
• Collaborate with various business stakeholders, software engineers, machine learning engineers, and analysts.
• Operate between Engineers and Analysts to unify both practices for analytics insight creation.

Who You Are:

• 8+ years of experience in Tech Support (Specialised in Monitoring and maintaining Data pipeline).
• Adept in market research methodologies and using data to deliver representative insights.
• Inquisitive, curious, understands how to query complicated data sets, move and combine data between databases.
• Deep SQL experience is a must.
• Exceptional communication skills with the ability to collaborate and translate between technical and non-technical needs.
• English Language Fluency and proven success working with teams in the U.S.
• Experience in designing, developing and operating configurable Data pipelines serving high-volume and velocity data.
• Experience working with public clouds like GCP/AWS.
• Good understanding of software engineering, DataOps, and data architecture, Agile and DevOps methodologies.
• Proficient with SQL, Python or JVM-based language, Bash.
• Experience with any of Apache open-source projects such as Spark, Druid, Beam, Airflow etc. and big data databases like BigQuery, Clickhouse, etc. 
• Ability to think big, take bets and innovate, dive deep, hire and develop the best talent, learn and be curious.
• Experience in debugging UI and Backend issues will be add on.

Review Criteria

• Strong Senior Data Engineer profile
• 4+ years of hands-on Data Engineering experience
• Must have experience owning end-to-end data architecture and complex pipelines
• Must have advanced SQL capability (complex queries, large datasets, optimization)
• Must have strong Databricks hands-on experience
• Must be able to architect solutions, troubleshoot complex data issues, and work independently
• Must have Power BI integration experience
• CTC has 80% fixed and 20% variable in their ctc structure

Preferred

• Worked on Call center data, understand nuances of data generated in call centers
• Experience implementing data governance, quality checks, or lineage frameworks
• Experience with orchestration tools (Airflow, ADF, Glue Workflows), Python, Delta Lake, Lakehouse architecture

Job Specific Criteria

• CV Attachment is mandatory
• Are you Comfortable integrating with Power BI datasets?
• We have an alternate Saturdays working. Are you comfortable to WFH on 1st and 4th Saturday?

Role & Responsibilities

We are seeking a highly experienced Senior Data Engineer with strong architectural capability, excellent optimisation skills, and deep hands-on experience in modern data platforms. The ideal candidate will have advanced SQL skills, strong expertise in Databricks, and practical experience working across cloud environments such as AWS and Azure. This role requires end-to-end ownership of complex data engineering initiatives, including architecture design, data governance implementation, and performance optimisation. You will collaborate with cross-functional teams to build scalable, secure, and high-quality data solutions.

Key Responsibilities-

• Lead the design and implementation of scalable data architectures, pipelines, and integration frameworks.
• Develop, optimise, and maintain complex SQL queries, transformations, and Databricks-based data workflows.
• Architect and deliver high-performance ETL/ELT processes across cloud platforms.
• Implement and enforce data governance standards, including data quality, lineage, and access control.
• Partner with analytics, BI (Power BI), and business teams to enable reliable, governed, and high-value data delivery.
• Optimise large-scale data processing, ensuring efficiency, reliability, and cost-effectiveness.
• Monitor, troubleshoot, and continuously improve data pipelines and platform performance.
• Mentor junior engineers and contribute to engineering best practices, standards, and documentation.

Ideal Candidate

• Proven industry experience as a Senior Data Engineer, with ownership of high-complexity projects.
• Advanced SQL skills with experience handling large, complex datasets.
• Strong expertise with Databricks for data engineering workloads.
• Hands-on experience with major cloud platforms — AWS and Azure.
• Deep understanding of data architecture, data modelling, and optimisation techniques.
• Familiarity with BI and reporting environments such as Power BI.
• Strong analytical and problem-solving abilities with a focus on data quality and governance
• Proficiency in python or another programming language in a plus.

ROLES AND RESPONSIBILITIES:

We are seeking a highly experienced Senior Data Engineer with strong architectural capability, excellent optimisation skills, and deep hands-on experience in modern data platforms. The ideal candidate will have advanced SQL skills, strong expertise in Databricks, and practical experience working across cloud environments such as AWS and Azure. This role requires end-to-end ownership of complex data engineering initiatives, including architecture design, data governance implementation, and performance optimisation. You will collaborate with cross-functional teams to build scalable, secure, and high-quality data solutions.

Key Responsibilities-

• Lead the design and implementation of scalable data architectures, pipelines, and integration frameworks.
• Develop, optimise, and maintain complex SQL queries, transformations, and Databricks-based data workflows.
• Architect and deliver high-performance ETL/ELT processes across cloud platforms.
• Implement and enforce data governance standards, including data quality, lineage, and access control.
• Partner with analytics, BI (Power BI), and business teams to enable reliable, governed, and high-value data delivery.
• Optimise large-scale data processing, ensuring efficiency, reliability, and cost-effectiveness.
• Monitor, troubleshoot, and continuously improve data pipelines and platform performance.
• Mentor junior engineers and contribute to engineering best practices, standards, and documentation.

IDEAL CANDIDATE:

• Proven industry experience as a Senior Data Engineer, with ownership of high-complexity projects.
• Advanced SQL skills with experience handling large, complex datasets.
• Strong expertise with Databricks for data engineering workloads.
• Hands-on experience with major cloud platforms — AWS and Azure.
• Deep understanding of data architecture, data modelling, and optimisation techniques.
• Familiarity with BI and reporting environments such as Power BI.
• Strong analytical and problem-solving abilities with a focus on data quality and governance
• Proficiency in python or another programming language in a plus.

PERKS, BENEFITS AND WORK CULTURE:

Our people define our passion and our audacious, incredibly rewarding achievements. The company is one of India’s most diversified Non-banking financial companies, and among Asia’s top 10 Large workplaces. If you have the drive to get ahead, we can help find you an opportunity at any of the 500+ locations we’re present in India.

Enterprise Data Architect - Dataeconomy (25+ Years Experience)

About Dataeconomy:

Dataeconomy is a rapidly growing company at the forefront of Information Technology. We are driven by data and committed to using it to make better decisions, improve our products, and deliver exceptional value to our customers.

Job Summary:

Dataeconomy seeks a seasoned and strategic Enterprise Data Architect to lead the company's data transformation journey. With 25+ years of experience in data architecture and leadership, you will be pivotal in shaping our data infrastructure, governance, and culture. You will leverage your extensive expertise to build a foundation for future growth and innovation, ensuring our data assets are aligned with business objectives and drive measurable value.

Responsibilities:

Strategic Vision and Leadership:

Lead the creation and execution of a long-term data strategy aligned with the company's overall vision and goals.

Champion a data-driven culture across the organization, fostering cross-functional collaboration and data literacy.

Advise senior leadership on strategic data initiatives and their impact on business performance.

Architecture and Modernization:

Evaluate and modernize the existing data architecture, recommending and implementing innovative solutions.

Design and implement a scalable data lake/warehouse architecture for future growth.

Advocate for and adopt cutting-edge data technologies and best practices.

ETL Tool Experience (8+ years):

Extensive experience in designing, developing, and implementing ETL (Extract, Transform, Load) processes using industry-standard tools such as Informatica PowerCenter, IBM DataStage, Microsoft SSIS, or open-source options like Apache Airflow.

Proven ability to build and maintain complex data pipelines that integrate data from diverse sources, transform it into usable formats, and load it into target systems.

Deep understanding of data quality and cleansing techniques to ensure the accuracy and consistency of data across the organization.

Data Governance and Quality:

Establish and enforce a comprehensive data governance framework ensuring data integrity, consistency, and security.

Develop and implement data quality standards and processes for continuous data improvement.

Oversee the implementation of master data management and data lineage initiatives.

Collaboration and Mentorship:

Mentor and guide data teams, including architects, engineers, and analysts, on data architecture principles and best practices.

Foster a collaborative environment where data insights are readily shared and acted upon across the organization.

Build strong relationships with business stakeholders to understand and translate their data needs into actionable solutions.

Qualifications:

Education: master’s degree in computer science, Information Systems, or related field; Ph.D. preferred.

Experience: 25+ years of experience in data architecture and design, with 10+ years in a leadership role.

Technical Skills:

Deep understanding of TOGAF, AWS, MDM, EDW, Hadoop ecosystem (MapReduce, Hive, HBase, Pig, Flume, Scoop), cloud data platforms (Azure Synapse, Google Big Query), modern data pipelines, streaming analytics, data governance frameworks.

Proficiency in programming languages (Java, Python, SQL), scripting languages (Bash, Python), data modelling tools (ER diagramming software), and BI tools.

Extensive expertise in ETL tools (Informatica PowerCenter, IBM DataStage, Microsoft SSIS, Apache Airflow)

Familiarity with emerging data technologies (AI/ML, blockchain), data security and compliance frameworks.

Soft Skills:

Outstanding communication, collaboration, and leadership skills.

Strategic thinking and problem-solving abilities with a focus on delivering impactful solutions.

Strong analytical and critical thinking skills.

Ability to influence and inspire teams to achieve goals.

• Design and implement effective database solutions and models to store and retrieve company data.
• Examine and identify database structural necessities by evaluating client operations, applications, and programming.
• Assess database implementation procedures to ensure they comply with internal and external regulations.
• Install and organize information systems to guarantee company functionality.
• Prepare accurate database design and architecture reports for management and executive teams.
• Oversee the migration of data from legacy systems to new solutions.
• Monitor the system performance by performing regular tests, troubleshooting, and integrating new features.
• Recommend solutions to improve new and existing database systems.
• Educate staff members through training and individual support.
• Offer support by responding to system problems in a timely manner.

Required Skills:

• Proven work experience as an Enterprise / Data / Analytics Architect - Data Platform in HANA XSA, XS, Data Intelligence and SDI
• Can work on new and existing architecture decision in HANA XSA, XS, Data Intelligence and SDI
• Well versed with data architecture principles, software / web application design, API design, UI / UX capabilities, XSA / Cloud foundry architecture
• In-depth understand of database structure (HANA in-memory) principles.
• In-depth understand of ETL solutions and data integration strategy.
• Excellent knowledge of Software and Application design, API, XSA, and microservices concepts

Roles & Responsibilities:

• Advise and ensure compliance of the defined Data Architecture principle.
• Identifies new technologies update and development tools including new release/upgrade/patch as required. 
• Analyzes technical risks and advises on risk mitigation strategy.
• Advise and ensures compliance to existing and development required data and reporting standard including naming convention.

The time window is ideally AEST (8 am till 5 pm) which means starting at 3:30 am IST. We understand it can be very early for an SME supporting from India. Hence, we can consider the candidates who can support from at least 7 am IST (earlier is possible).

Company Profile:

Easebuzz is a payment solutions (fintech organisation) company which enables online merchants to accept, process and disburse payments through developer friendly APIs. We are focusing on building plug n play products including the payment infrastructure to solve complete business problems. Definitely a wonderful place where all the actions related to payments, lending, subscription, eKYC is happening at the same time.

We have been consistently profitable and are constantly developing new innovative products, as a result, we are able to grow 4x over the past year alone. We are well capitalised and have recently closed a fundraise of $4M in March, 2021 from prominent VC firms and angel investors. The company is based out of Pune and has a total strength of 180 employees. Easebuzz’s corporate culture is tied into the vision of building a workplace which breeds open communication and minimal bureaucracy. An equal opportunity employer, we welcome and encourage diversity in the workplace. One thing you can be sure of is that you will be surrounded by colleagues who are committed to helping each other grow.

Easebuzz Pvt. Ltd. has its presence in Pune, Bangalore, Gurugram.

Salary: As per company standards.

Designation: Data Engineering

Location: Pune

Experience with ETL, Data Modeling, and Data Architecture

Design, build and operationalize large scale enterprise data solutions and applications using one or more of AWS data and analytics services in combination with 3rd parties
- Spark, EMR, DynamoDB, RedShift, Kinesis, Lambda, Glue.

Experience with AWS cloud data lake for development of real-time or near real-time use cases

Experience with messaging systems such as Kafka/Kinesis for real time data ingestion and processing

Build data pipeline frameworks to automate high-volume and real-time data delivery

Create prototypes and proof-of-concepts for iterative development.

Experience with NoSQL databases, such as DynamoDB, MongoDB etc

Create and maintain optimal data pipeline architecture,

Identify, design, and implement internal process improvements: automating manual processes, optimizing data delivery, re-designing infrastructure for greater scalability, etc.

Build the infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of data sources using SQL and AWS ‘big data’ technologies.

Build analytics tools that utilize the data pipeline to provide actionable insights into customer acquisition, operational efficiency and other key business performance metrics.

Work with stakeholders including the Executive, Product, Data and Design teams to assist with data-related technical issues and support their data infrastructure needs.

Keep our data separated and secure across national boundaries through multiple data centers and AWS regions.

Create data tools for analytics and data scientist team members that assist them in building and optimizing our product into an innovative industry leader.

Evangelize a very high standard of quality, reliability and performance for data models and algorithms that can be streamlined into the engineering and sciences workflow

Build and enhance data pipeline architecture by designing and implementing data ingestion solutions.

Employment Type

Full-time

• 6+ years of recent hands-on Java development
• Developing data pipelines in AWS or Google Cloud
• Java, Python, JavaScript programming languages
• Great understanding of designing for performance, scalability, and reliability of data intensive application
• Hadoop MapReduce, Spark, Pig. Understanding of database fundamentals and advanced SQL knowledge.
• In-depth understanding of object oriented programming concepts and design patterns
• Ability to communicate clearly to technical and non-technical audiences, verbally and in writing
• Understanding of full software development life cycle, agile development and continuous integration
• Experience in Agile methodologies including Scrum and Kanban

Pingahla is recruiting business intelligence Consultants/Senior consultants who can help us with Information Management projects (domestic, onshore and offshore) as developers and team leads. The candidates are expected to have 3-6 years of experience with Informatica Power Center/Talend DI/Informatica Cloud and must be very proficient with Business Intelligence in general. The job is based out of our Pune office.

Responsibilities:

• Manage the customer relationship by serving as the single point of contact before, during and after engagements.
• Architect data management solutions.
• Provide technical leadership to other consultants and/or customer/partner resources.
• Design, develop, test and deploy data integration solutions in accordance with customer’s schedule.
• Supervise and mentor all intermediate and junior level team members.
• Provide regular reports to communicate status both internally and externally.
• Qualifications:
• A typical profile that would suit this position would be if the following background:
• A graduate from a reputed engineering college 
• An excellent I.Q and analytical skills and should be able to grasp new concepts and learn new technologies.
• A willingness to work with a small team in a fast-growing environment.
• A good knowledge of Business Intelligence concepts

Mandatory Requirements:

• Knowledge of Business Intelligence
• Good knowledge of at least one of the following data integration tools - Informatica Powercenter, Talend DI, Informatica Cloud
• Knowledge of SQL
• Excellent English and communication skills
• Intelligent, quick to learn new technologies
• Track record of accomplishment and effectiveness with handling customers and managing complex data management needs