Lead Data Engineer (Insurance / Financial Services)

Job Title: Lead Data Engineer (Insurance / Financial Services)

Location: Jersey City, NJ

Employment Type: Full-Time

Salary: $60/hr CTC

Industry: Insurance / Financial Services

We are seeking an experienced Lead Data Engineer to join our Data & Analytics practice supporting enterprise-scale Insurance and Financial Services initiatives. This role is ideal for professionals with strong expertise in AWS, Snowflake, PySpark, SQL, and cloud data engineering who can lead technical delivery while coordinating with onshore/offshore teams and client stakeholders.

The ideal candidate will combine deep hands-on data engineering expertise with strong leadership, stakeholder management, and cloud modernization experience to deliver scalable, high-performance data solutions.

Top Required Skills:

• AWS Data Engineering (S3, Glue, EMR, Redshift, Lambda)

• Snowflake, PySpark & Advanced SQL

• Data Migration, Cloud Modernization & Team Leadership

Key Responsibilities:

Technical Delivery

• Design, develop, and maintain scalable end-to-end data pipelines using PySpark, Snowflake, and AWS cloud services.

• Architect enterprise ELT/ETL solutions and cloud-native data warehouse platforms supporting insurance analytics.

• Lead cloud migration and legacy modernization initiatives for enterprise data platforms.

• Develop and optimize complex SQL transformations, stored procedures, and data validation frameworks.

• Design scalable dimensional data models using Kimball, Inmon, Data Vault, Star Schema, and Snowflake Schema methodologies.

• Establish data engineering standards, coding best practices, and technical documentation.

• Troubleshoot production issues and optimize performance across data pipelines and cloud infrastructure.

Team Leadership & Stakeholder Engagement

• Coordinate daily activities across onshore and offshore data engineering teams to ensure successful project delivery.

• Serve as the primary technical point of contact for business stakeholders and project leadership.

• Translate business requirements into scalable technical solutions and engineering deliverables.

• Facilitate requirement gathering sessions, sprint planning, backlog refinement, and project status meetings.

• Communicate project progress, risks, dependencies, and mitigation plans to leadership and client stakeholders.

• Mentor junior engineers, perform code reviews, and promote engineering best practices.

• Collaborate with Architects, Data Analysts, QA teams, and Product Owners throughout the project lifecycle.

Required Qualifications:

• 6–9 years of progressive experience in Data Engineering.

• Strong expertise with Snowflake including data modeling, performance tuning, and optimization.

• Hands-on experience with AWS services including:

  • Amazon S3

  • AWS Glue

  • AWS Lambda

  • Amazon EMR

  • Amazon Redshift

  • AWS Step Functions

  • Amazon CloudWatch

• Strong experience with Apache Spark and PySpark for distributed data processing.

• Advanced SQL skills including complex query optimization, transformations, and dimensional modeling.

• Expertise designing enterprise data warehouse architectures using Kimball, Inmon, Data Vault, Star Schema, and Snowflake Schema methodologies.

• Experience leading cloud migration and enterprise data modernization initiatives.

• Experience with orchestration tools such as dbt, Apache Airflow, AWS Glue, or similar platforms.

• Strong Python programming skills for data engineering and automation.

• Experience working in Agile/Scrum environments.

• Excellent communication, stakeholder management, and leadership skills.

• Experience coordinating distributed onshore/offshore engineering teams.

Preferred Qualifications:

• Experience in Insurance, Financial Services, or other regulated industries.

• Experience building enterprise cloud data platforms and modern data lake architectures.

• Exposure to CI/CD, Infrastructure as Code, and DevOps practices for data engineering.

• Experience mentoring technical teams and driving engineering excellence.

Education:

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

If you are a hands-on Lead Data Engineer with expertise in AWS, Snowflake, PySpark, and enterprise data modernization, and you''re looking to work on large-scale Insurance and Financial Services data initiatives, we''d love to hear from you.

Apply today with your updated resume.