Data Engineering Tech Lead

Tata Consultancy Services; Jersey City (NJ); On-site; USD 180,000 - 210,000; Full time

Benefits offered by this job

Discretionary Annual Incentive

Comprehensive Medical Coverage

Family Leave & Parental Support

Insurance Options: Auto & Home

Certification & Training Reimbursement

Paid Vacation & Holidays

401K Plan + Bonus

Job summary

Tata Consultancy Services is hiring for a senior data engineering role in New Jersey to design and govern cloud-native analytics platforms for Property & Casualty insurance. You will lead end-to-end data platform initiatives, spanning data lakes, lakehouses, and cloud data warehouses, with emphasis on real-time processing and GenAI-enabled workflows.

Ideal candidates will bring hands-on experience with AWS, Snowflake, and data tooling, plus strong stakeholder management across underwriting,

Qualifications

• Strong experience designing, implementing, and governing modern cloud-native data platforms.
• Proven expertise in Data Warehousing, Data Modeling, ETL/ELT; data integration and data quality.
• Hands-on experience with Python, PySpark, Informatica, DataStage, AWS Glue, Snowflake.
• Leadership in delivering data platforms like Data Lakes and Lakehouses; real-time data processing.

Responsibilities

• Design, architect, and implement scalable, secure data platforms for insurance analytics.
• Partner with stakeholders to translate objectives into scalable data architecture and roadmaps.
• Evaluate emerging data technologies and lead modernization efforts using AWS Glue, Snowflake, and GenAI.

Skills

Cloud data platforms

AWS

Snowflake

ETL/ELT

Data Warehousing

Data Modeling

Python

PySpark

GenAI

AI in SDLC

Data pipelines

Stakeholder management

Education

Bachelor's degree in Computer Science

Tools

AWS Glue

Informatica

DataStage

PySpark

Snowflake

Duck Creek

Guidewire

Job description

• 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, DataStage, 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, Lakehouses, 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, lakehouses, 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.

Job Description

Must Have Technical/Functional Skills

• 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, DataStage, 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, Lakehouses, 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.

Roles & Responsibilities

• 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, lakehouses, 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.

TCS Employee Benefits Summary

• Discretionary Annual Incentive.
• Comprehensive Medical Coverage: Medical & Health, Dental & Vision, Disability Planning & Insurance, Pet Insurance Plans.
• Family Support: Maternal & Parental Leaves.
• Insurance Options: Auto & Home Insurance, Identity Theft Protection.
• Convenience & Professional Growth: Commuter Benefits & Certification & Training Reimbursement.
• Time Off: Vacation, Time Off, Sick Leave & Holidays.
• Legal & Financial Assistance: Legal Assistance, 401K Plan, Performance Bonus, College Fund, Student Loan Refinancing.

Salary Range: $180,000 - $210,000 a year

Qualifications:

BACHELOR OF COMPUTER SCIENCE