Data Engineering Tech Lead
Job in
Jersey City, Hudson County, New Jersey, 07390, USA
Listed on 2026-09-13
Listing for:
Tata Consultancy Services
Full Time
position Listed on 2026-09-13
Job specializations:
-
IT/Tech
Data Engineering, Data Warehousing, AWS, Cloud Computing: Infrastructure & Operations
Job Description & How to Apply Below
- Strong experience designing, implementing, and governing modern cloud-native data platforms using AWS, AWS Glue, Snowflake, and related cloud data services. Experience in large-scale data modernization and migration initiatives is preferred.
- Proven expertise in Data Warehousing, Data Modeling, ETL/ELT architecture, data integration, data quality, metadata management, and scalable data pipeline design for enterprise analytics and operational workloads
- Hands-on experience developing and optimizing data solutions using Python, PySpark, Informatica, Data Stage, AWS Glue, Snowflake, and related cloud-native data engineering technologies. Ability to guide engineering teams on architecture, coding standards, and implementation best practices.
- Demonstrated leadership in architecting and delivering solutions on modern data platforms, including Data Lakes, Lake houses, Cloud Data Warehouses, and real-time data processing ecosystems. Hands-on implementation experience is required.
- Strong understanding of Generative AI, Agentic AI, and AI-enabled engineering concepts, including practical application of GenAI across the Software Development Lifecycle (SDLC), data engineering workflows, reverse engineering, migration acceleration, code generation, testing, documentation, and productivity optimization.
- Familiarity with Insurance industry platforms and core systems, including Policy Administration, Claims, Billing, Underwriting, Data & Analytics ecosystems, and digital modernization initiatives. Knowledge of platforms such as Guidewire, Duck Creek, Majesco, or equivalent insurance systems is desirable.
- Strong consulting, solutioning, and stakeholder management skills with the ability to work closely with data, cloud, architecture and business to define transformation roadmaps and deliver business value through data-driven solutions.
- Design, architect, and implement scalable, secure, and high-performance enterprise data platforms that support the evolving needs of the Property & Casualty Insurance business, including Underwriting, Claims, Billing, Actuarial, Finance, and Analytics functions.
- Partner closely with business stakeholders, including Underwriting, Actuarial, Claims, Data Office, and Technology teams, to translate business objectives into scalable data architecture, engineering solutions, and actionable roadmaps.
- Evaluate emerging data technologies; solution evaluations
- Relevant technologies in current insurance data modernization efforts include AWS Glue, PySpark, Snowflake, GenAI agents, and modern data platforms. - Lead modernization of legacy data ecosystems and drive migration to cloud-native platforms, data lakes, lake houses, and modern data warehouses leveraging AWS and related cloud technologies. Modernization efforts involving AWS Glue, Snowflake, and cloud-native architectures have been identified as key transformation priorities.
- Define enterprise data integration strategies across core insurance platforms such as Duck Creek, and adjacent enterprise systems, while enabling seamless integration with third-party data sources and industry providers.
- Strong experience designing, implementing, and governing modern cloud-native data platforms using AWS, AWS Glue, Snowflake, and related cloud data services. Experience in large-scale data modernization and migration initiatives is preferred.
- Proven expertise in Data Warehousing, Data Modeling, ETL/ELT architecture, data integration, data quality, metadata management, and scalable data pipeline design for enterprise analytics and operational workloads
- Hands-on experience developing and optimizing data solutions using Python, PySpark, Informatica, Data Stage, AWS Glue, Snowflake, and related…
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