Director - Data Engineering at Searce Inc · Bengaluru (Bangalore), Mumbai, Pune · 10 - 18 years · Profitable · Posted 25 Jun 2026
Amazon Web Services (AWS)
Python
ScalaDirector - 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.
Shubham Vishwakarma
Full Stack Developer - Averlon
About Searce Inc
About
What is ‘searce’
Searce means ‘a fine sieve’ & indicates ‘to refine, to analyze, to improve’. It signifies our way of working: To improve to the finest degree of excellence, ‘solving for better’ every time. Searcians are passionate improvers & solvers who love to question the status quo.
The primary purpose of all of us, at Searce, is driving intelligent, impactful & futuristic business outcomes using new-age technology. This purpose is driven passionately by HAPPIER people who aim to become better, everyday.
What we do
Searce is a modern tech consulting firm that empowers clients to futurify their businesses, leveraging Cloud, AI & Analytics.
- We are a category defining niche’ cloud-native technology consulting company, specializing in modernizing (improve, automate & transform) the full-scope of infra, app, process & work
- We partner with clients in their ‘beyond x’ journey to drive intelligent, impactful & futuristic business outcomes
- We are the most preferred tech partner of choice when it comes to ‘solving for better’ for the new-age tech startups & digital enterprises, leading disruption in their industries
- Our Service Offerings: We offer Advanced Cloud, Data & App Modernization, Cloud Consulting, Management & Improvement (DevOps, SysOps & Cloud Managed Services), Applied AI & Analytics services
- As one of the top 5 niche’ full scope global partners for Google Cloud & a preferred partner for AWS, we are the most preferred ‘engineering-led’ tech company of choice when it comes to solving complex business problems.
Who we are
We are passionate improvers, solvers & futurists. Driven by our engineering excellence mindset, we care most about delivering intelligent, impactful & futuristic business outcomes. Searcians are motivated by continuous improvement & solving for better in everything we do.
At the core, a Searcian is self-driven to become better, everyday. In passionate pursuit of the finest degree of excellence we drive exceptional outcomes in everything we do.
We believe that trust is the most important value. We also believe that we need to ‘earn the trust’, everytime one engages with us. And earning trust for us is far more important than anything else. We aim to be the *most trusted* tech consulting partner for our clients.
We are HAPPIER at heart. Humble, Adaptable, Positive, Passionate, Innovative, Excellence focused, & Responsible. We live the HAPPIER Culture Code.
Being HAPPIER.
How we work
- Customers. Partners. Our aim is to build relationships with customers for life. And meaningfully improve the life of every customer.
- We do what we say. We say what we do. We are uncomfortably honest and transparent. Being genuine wins trust & makes people happier.
- Mistakes are encouraged. We make mistakes. Tons of those. Everyday. And we don’t mind apologizing to our juniors, peers or superiors. We are no ego-doers.
- Underpromise. Overdeliver. We work with a deep desire to go above and beyond in everything we do. Everytime.
So, If you are passionate about tech, future & what you read above (we really are!), apply here to experience the ‘Art of Possible’
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JavaCompany Name – Wissen Technology
Group of companies in India – Wissen Technology & Wissen Infotech
Work Location – Whitefield, Bangalore
Website and Company profile:
www.wissen.com
LinkedIn Page:
https://www.linkedin.com/company/wissen-technology/
While you may already know about Wissen and the company history, here is a quick rundown for you.
About Wissen Technology:
· The Wissen Group was founded in the year 2000. Wissen Technology, a part of Wissen Group, was established in the year 2015.
· Wissen Technology is a specialized technology company that delivers high-end consulting for organizations in the Banking & Finance, Telecom, and Healthcare domains. We help clients build world class products.
· Our workforce has highly skilled professionals, with leadership and senior management executives who have graduated from Ivy League Universities like Wharton, MIT, IITs, IIMs, and NITs and with rich work experience in some of the biggest companies in the world.
· Wissen Technology has grown its revenues by 400% in these five years without any external funding or investments.
· Globally present with offices US, India, UK, Australia, Mexico, and Canada.
· We offer an array of services including Application Development, Artificial Intelligence & Machine Learning, Big Data & Analytics, Visualization & Business Intelligence, Robotic Process Automation, Cloud, Mobility, Agile & DevOps, Quality Assurance & Test Automation.
· Wissen Technology has been certified as a Great Place to Work®.
· Wissen Technology has been voted as the Top 20 AI/ML vendor by CIO Insider in 2020.
· Over the years, Wissen Group has successfully delivered $650 million worth of projects for more than 20 of the Fortune 500 companies.
· We have served client across sectors like Banking, Telecom, Healthcare, Manufacturing, and Energy. They include likes of Morgan Stanley, Goldman Sachs, MSCI, StateStreet, Flipkart, Swiggy, Trafigura, GE to name a few.
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Key Responsibilities
- Build and maintain data transformation pipelines using java Spark
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- Implement data quality checks, testing, and monitoring for pipeline. Good to have exposer into managing metadata, cataloguing, and lineage
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- Expertise/working knowledge in Spark and HBase(semantic layer, virtual datasets, Reflections)
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- Proficiency in Java
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Nice-to-Have Skills
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Amazon Web Services (AWS)Job description: Data Architect – Databricks / AWS
Job Summary
We are looking for an experienced Data Architect to define and drive the target data architecture for the Horizon MVP and its future evolution. The role will be responsible for designing a scalable, secure, governed cloud data platform covering ingestion, storage, processing, analytics, APIs, and downstream data consumption.
The architect will work closely with Data Engineering, Backend, DevOps, QA, and business stakeholders to establish architecture standards and ensure the platform is ready for advanced analytics, AI/ML, vector storage, and future LLM-based capabilities.
- Job Title: Data Architect
- Experience: 8+ Years
- Relevant Architecture Experience: 3+ Years in Data Architecture
- Location: Chennai / Pune
- Work Mode: Hybrid – 3 Days WFO
- Budget: Up to 24 LPA
- Payroll: Haparz
- Notice Period: Immediate Preferred
Key Responsibilities
- Define the target data architecture for the Horizon MVP and establish an architecture roadmap for future scalability.
- Design end-to-end architecture covering data ingestion, storage, processing, serving, reporting, APIs, and downstream applications.
- Establish canonical data models and schemas for travel signals, corridors, sources, evidence, scores, and generated insights.
- Define data normalization strategies for structured, semi-structured, and unstructured data from multiple external sources.
- Design and govern the Databricks platform architecture, including Unity Catalog, data schemas, access controls, and governance standards.
- Establish data-retention, lineage, data-quality, security, privacy, and compliance controls.
- Define secure integration patterns between Databricks, AWS PRODIGY, SharePoint, external APIs, and downstream applications.
- Design scalable data processing for 30-day signal windows, convergence/divergence scoring, corridor ranking, and spike detection.
- Define architecture patterns that support future vector storage, embeddings, LLM integration, and multi-year analytics.
- Design reliable batch and API-driven ingestion frameworks for structured and unstructured data.
- Review technical designs, identify architectural risks, and provide technical direction to engineering teams.
- Guide backend, data engineering, DevOps, and QA teams in implementing architecture standards.
- Ensure architecture decisions align with enterprise security, RBAC, PII handling, privacy, and operational requirements.
- Communicate architecture decisions, trade-offs, and technical recommendations effectively to technical and business stakeholders.
What We’re Looking For
- 8+ years of experience in data engineering, data platforms, or data architecture, with at least 3+ years in a Data Architect capacity.
- Strong hands-on experience designing cloud-based data platforms, lakehouses, or analytical platforms.
- Advanced knowledge of Databricks, Apache Spark/PySpark, Delta Lake, and Unity Catalog.
- Strong understanding of AWS data services, IAM, networking, and secure cloud integration patterns.
- Strong expertise in data modelling, metadata management, data lineage, data quality, retention, and governance.
- Experience architecting batch and API-based ingestion pipelines for structured, semi-structured, and unstructured data.
- Understanding of AI/ML workloads, feature pipelines, vector databases, embeddings, and LLM integration patterns.
- Experience designing APIs and downstream data-serving architectures.
- Strong knowledge of PII protection, RBAC, data privacy, and enterprise security controls.
- Excellent architectural communication and stakeholder-management skills.
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Full Stack Developer - Averlon