Lead Data Engineer

EXL; Jersey City (NJ); On-site; USD 100,000 - 140,000; Full time

Benefits offered by this job

Job summary

EXL is seeking an experienced Lead Data Engineer to drive complex data initiatives within our insurance data and analytics practice. You will lead design and implementation of cloud-based data pipelines, mentor engineers, and coordinate onshore/offshore teams to deliver enterprise modernization projects.

The role requires 6–9 years in data engineering, hands-on PySpark, Snowflake, AWS, and strong SQL, with excellent stakeholder communication.

Qualifications

• 6–9 years of progressive data engineering experience
• Experience coordinating distributed teams across time zones
• Experience engaging with non-technical stakeholders
• Exposure to Agile/Scrum delivery
• Bachelor's degree in CS/IS/Engineering

Responsibilities

• Design and implement end-to-end data pipelines with PySpark, Snowflake, and AWS
• Migrate legacy data to cloud-native platforms
• Develop and review SQL transformations and data quality checks
• Establish data engineering standards and pipeline docs
• Mentor engineers and perform code reviews
• Coordinate onshore/offshore teams and report to stakeholders

Skills

Snowflake modeling

AWS services

PySpark

Apache Spark

SQL

Data warehousing

Data migration

Python

dbt

Apache Airflow

Education

Bachelor's degree in CS/IS/Engineering

Tools

dbt

Apache Airflow

AWS Glue

Snowflake

Python

ETL

Job description

We are seeking an experienced Lead Data Engineer to support complex data engineering initiatives within our insurance data and analytics practice. This role combines deep technical expertise with strong coordination skills, working closely with onshore and offshore teams, business stakeholders, and project leadership to deliver enterprise data modernization and migration programs. The candidate will serve as a technical point of contact for cross-functional teams while remaining hands-on with cloud data technologies.

Key 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

Education

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

For more information on benefits and what we offer please visit us at https://www.exlservice.com/us-careers-and-benefits

Base Compensation Range: 100,000 – 140,000

The posted range is the hiring range for this role — a subset of the broader range available to employees over time — and reflects base salary across our national hiring scale. Final offers are based on several factors, including the candidate's skills and experience, internal pay equity, work location, market conditions for the role, and the specific scope and responsibilities of the position. The top of the range is reserved for candidates who notably exceed the requirements; the lower end applies to those with less experience or fewer preferred qualifications. For positions based in higher-cost zones (e.g., California, New York, New Jersey), actual compensation may exceed the posted range; your recruiter will share specifics during the process.