Lead Data Engineer

• Design and implement end-to-end data pipelines using PySpark, Snowflake, and AWS cloud services
• Architect scalable ELT/ETL workflows and data warehouse models supporting insurance analytics use cases
• Drive data migration and modernization efforts from legacy environments to cloud-native platforms
• Develop and review complex SQL transformations, stored procedures, and data quality validation frameworks
• Establish and enforce data engineering standards, coding best practices, and pipeline documentation
• Provide hands-on troubleshooting and performance optimization across the data stack

Team Coordination & Stakeholder Engagement

• Coordinate day-to-day activities across onshore and offshore data engineering teams to ensure timely delivery
• Serve as a technical point of contact for business stakeholders, translating requirements into engineering deliverables
• Facilitate requirement-gathering sessions, sprint planning, and status updates with project teams
• Communicate project progress, risks, and dependencies to project managers and client stakeholders
• Mentor junior engineers and conduct code reviews to uphold quality standards
• Collaborate with data architects, analysts, and QA teams throughout the project lifecycle

• Deep experience with Snowflake including data modeling, performance tuning
• Proficiency with AWS services - S3, Glue, Lambda, EMR, Redshift, Step Functions, CloudWatch
• Strong experience building distributed data processing frameworks with Apache Spark / PySpark
• Advanced SQL skills - complex transformations, query optimization, and dimensional modeling
• Expertise in DWH design patterns - Kimball, Inmon, Data Vault, star and snowflake schemas
• Demonstrated experience leading or contributing to cloud migration and legacy modernization programs
• Familiarity with tools such as dbt, Apache Airflow, AWS Glue, or similar orchestration frameworks

Solid Python programming for data engineering and automation tasks

Qualifications: Experience Requirements

• 6-9 years of progressive experience in data engineering
• Prior experience in insurance, financial services, or regulated industries preferred
• Experience coordinating distributed teams across time zones (onshore/offshore model)
• Demonstrated ability to engage with non-technical stakeholders and translate business requirements
• Exposure to Agile/Scrum delivery methodology

Education

• Bachelor’s degree in Computer Science, Information Systems, Engineering, or a related field