Data Engineering Tech Lead

• 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