Senior Data Engineer: Cloud ETL (PySpark, Snowflake)

DataJobs; Jersey City (NJ); On-site; USD 100,000 - 125,000; Full time

Job summary

EXL Service is seeking a Senior Data Engineer to support the insurance data and analytics practice in a hands-on, onsite capacity in Jersey City, NJ. You will design and implement end-to-end data pipelines using PySpark, Snowflake, and AWS to power analytics workloads.

You will build scalable ELT/ETL workflows, craft data warehouse models, and ensure data quality and production readiness through validation frameworks and robust coding standards.

Qualifications

• Bachelor's degree in Computer Science, Information Systems, Engineering, or a related field.
• Experience with PySpark, Snowflake, and AWS.
• Strong SQL skills and experience with ETL/ELT workflows.

Responsibilities

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

Skills

PySpark

End-to-end pipelines

Data quality validation

Performance optimization

Data modeling

Education

Bachelor's degree in CS/IS/Engineering or related field

Tools

Snowflake

AWS

ELT/ETL

SQL

Job description

EXL Service is seeking a Senior Data Engineer to support the insurance data and analytics practice in a hands-on, onsite capacity in Jersey City, NJ. You will design and implement end-to-end data pipelines using PySpark, Snowflake, and AWS to power analytics workloads.

You will build scalable ELT/ETL workflows, craft data warehouse models, and ensure data quality and production readiness through validation frameworks and robust coding standards.