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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.

We are looking for a skilled Data Engineer / Data Warehouse Engineer to design, develop, and maintain scalable data pipelines and enterprise data warehouse solutions. The role involves close collaboration with business stakeholders and BI teams to deliver high-quality data for analytics and reporting.

Key Responsibilities

• Collaborate with business users and stakeholders to understand business processes and data requirements
• Design and implement dimensional data models, including fact and dimension tables
• Identify, design, and implement data transformation and cleansing logic
• Build and maintain scalable, reliable, and high-performance ETL/ELT pipelines
• Extract, transform, and load data from multiple source systems into the Enterprise Data Warehouse
• Develop conceptual, logical, and physical data models, including metadata, data lineage, and technical definitions
• Design, develop, and maintain ETL workflows and mappings using appropriate data load techniques
• Provide high-level design, research, and effort estimates for data integration initiatives
• Provide production support for ETL processes to ensure data availability and SLA adherence
• Analyze and resolve data pipeline and performance issues
• Partner with BI teams to design and develop reports and dashboards while ensuring data integrity and quality
• Translate business requirements into well-defined technical data specifications
• Work with data from ERP, CRM, HRIS, and other transactional systems for analytics and reporting
• Define and document BI usage through use cases, prototypes, testing, and deployment
• Support and enhance data governance and data quality processes
• Identify trends, patterns, anomalies, and data quality issues, and recommend improvements
• Train and support business users, IT analysts, and developers
• Lead and collaborate with teams spread across multiple locations

Required Skills & Qualifications

• Bachelor’s degree in Computer Science or a related field, or equivalent work experience
• 3+ years of experience in Data Warehousing, Data Engineering, or Data Integration
• Strong expertise in data warehousing concepts, tools, and best practices
• Excellent SQL skills
• Strong knowledge of relational databases such as SQL Server, PostgreSQL, and MySQL
• Hands-on experience with Google Cloud Platform (GCP) services, including:

1. BigQuery
2. Cloud SQL
3. Cloud Composer (Airflow)
4. Dataflow
5. Dataproc
6. Cloud Functions
7. Google Cloud Storage (GCS)

• Experience with Informatica PowerExchange for Mainframe, Salesforce, and modern data sources
• Strong experience integrating data using APIs, XML, JSON, and similar formats
• In-depth understanding of OLAP, ETL frameworks, Data Warehousing, and Data Lakes
• Solid understanding of SDLC, Agile, and Scrum methodologies
• Strong problem-solving, multitasking, and organizational skills
• Experience handling large-scale datasets and database design
• Strong verbal and written communication skills
• Experience leading teams across multiple locations

Good to Have

• Experience with SSRS and SSIS
• Exposure to AWS and/or Azure cloud platforms
• Experience working with enterprise BI and analytics tools

Why Join Us

• Opportunity to work on large-scale, enterprise data platforms
• Exposure to modern cloud-native data engineering technologies
• Collaborative environment with strong stakeholder interaction
• Career growth and leadership opportunities

Role & Responsibilities:

We are looking for a strong Data Engineer to join our growing team. The ideal candidate brings solid ETL fundamentals, hands-on pipeline experience, and cloud platform proficiency — with a preference for GCP / BigQuery expertise.

Responsibilities:

• Design, build, and maintain scalable data pipelines and ETL/ELT workflows
• Work with Dataform or DBT to implement transformation logic and data models
• Develop and optimize data solutions on GCP (BigQuery, GCS) or AWS/Azure
• Support data migration initiatives and data mesh architecture patterns
• Collaborate with analysts, scientists, and business stakeholders to deliver reliable data products
• Apply data governance and quality best practices across the data lifecycle
• Troubleshoot pipeline issues and drive proactive monitoring and resolution

Ideal Candidate:

• Strong Data Engineer Profile
• Must have 6+ years of hands-on experience in Data Engineering, with strong ownership of end-to-end data pipeline development.
• Must have strong experience in ETL/ELT pipeline design, transformation logic, and data workflow orchestration.
• Must have hands-on experience with any one of the following: Dataform, dbt, or BigQuery, with practical exposure to data transformation, modeling, or cloud data warehousing.
• Must have working experience on any cloud platform: GCP (preferred), AWS, or Azure, including object storage (GCS, S3, ADLS).
• Must have strong SQL skills with experience in writing complex queries and optimizing performance.
• Must have programming experience in Python and/or SQL for data processing.
• Must have experience in building and maintaining scalable data pipelines and troubleshooting data issues.
• Exposure to data migration projects and/or data mesh architecture concepts.
• Experience with Spark / PySpark or large-scale data processing frameworks.
• Experience working in product-based companies or data-driven environments.
• Bachelor’s or Master’s degree in Computer Science, Engineering, or related field.

NOTE:

• There will be an interview drive scheduled on 28th and 29th March 2026, and if shortlisted, they will be expected to be available on these Interview dates. Only Immediate joiners are considered.

Role: Project Manager

Experience: 8-10 Years

Location: Mumbai

Company Profile:



Exponentia.ai is an AI tech organization with a presence across India, Singapore, the Middle East, and the UK. We are an innovative and disruptive organization, working on cutting-edge technology to help our clients transform into the enterprises of the future. We provide artificial intelligence-based products/platforms capable of automated cognitive decision-making to improve productivity, quality, and economics of the underlying business processes. Currently, we are rapidly expanding across machine learning, Data Engineering and Analytics functions. Exponentia.ai has developed long-term relationships with world-class clients such as PayPal, PayU, SBI Group, HDFC Life, Kotak Securities, Wockhardt and Adani Group amongst others.

One of the top partners of Data bricks, Azure, Cloudera (leading analytics player) and Qlik (leader in BI technologies), Exponentia.ai has recently been awarded the ‘Innovation Partner Award’ by Qlik and "Excellence in Business Process Automation Award" (IMEA) by Automation Anywhere.

Get to know more about us at http://www.exponentia.ai and https://in.linkedin.com/company/exponentiaai 

Role Overview:

·        Project manager shall be responsible to oversee and take responsibility for the successful delivery of a range of projects in Business Intelligence, Data warehousing, and Analytics/AI-ML.

·        Project manager is expected to manage the project and lead the teams of BI engineers, data engineers, data scientists and application developers.

Job Responsibilities:

·        Efforts estimation, creating a project plan, planning milestones, activities and tracking the progress.

·        Identify risks and issues. Come up with a mitigation plan.

·        Status reporting to both internal and external stakeholders.

·        Communicate with all stakeholders.

·        Manage end-to-end project lifecycle - requirements gathering, design, development, testing and go-live.

·        Manage end-to-end BI or data warehouse projects.

·        Must have experience in running Agile-based project development.

Technical skills

·        Experience in Business Intelligence Data warehousing or Analytics projects.

·        Understand data lake and data warehouse solutions including ETL pipelines.

·        Good to have - Knowledge of Azure blob storage, azure data factory and Synapse analytics.

·        Good to have - Knowledge of Qlik Sense or Power BI

·        Good to have - Certified in PMP/Prince 2 / Agile Project management.

·        Excellent written and verbal communication skills.

 Education:

MBA, B.E. or B. Tech. or MCA degree