Role: Senior Data Engineer
Location: California, New York, New Jersey
Duration: Fulltime
Responsibilities
Technical Delivery
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
Required Skills & Qualifications
Technical Skills
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
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
Qualifications
Bachelor's degree in Computer Science, Information Systems, Engineering, or a related field
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