Remote Data Engineer — AWS, PySpark & ETL

Comcast; Philadelphia (Philadelphia County); On-site; USD 120,000 - 170,000; Full time

Job summary

Comcast Advertising seeks a data engineer to join a fully remote team. You will perform data engineering in an AWS cloud environment, handling S3, RDS, Lambda, and Secrets Manager, and you will work with SQL, ETL with Python/PySpark, and API development.

Responsibilities include building and maintaining data pipelines, using SAFe with CI/CD tooling, and collaborating across teams to ensure data quality and SLA compliance.

Qualifications

• Bachelor's degree in Computer Science, Engineering, or related technical field.
• 2+ years of experience performing data engineering in an AWS environment (S3, RDS, Lambda, CloudWatch, Secrets Manager).
• Experience with SQL CRUD operations, joins, aggregations, window functions, and SQL categories (DDL, DML, DCL, DQL, TCL).
• Proficiency with MS Office tools and API development; ETL with Python, PySpark, Spark; version control with GitHub.

Responsibilities

• Perform data engineering in AWS using S3, RDS, Lambda, CloudWatch, and Secrets Manager.
• Write and optimize SQL including DDL, DML, DCL, DQL, and TCL; use joins, aggregations, and window functions.
• Develop and consume APIs; perform ETL with Python, PySpark, Spark; manage code with GitHub.
• Utilize JIRA, Aha, ServiceNow, and Confluence for planning, documentation, and incident management; build CI/CD with Concourse.
• Work in a DevOps environment with Terraform, SAFe, and data-platform optimizations; monitor data quality and SLAs.

Skills

SAFe

GitHub

Python

Education

Bachelor's degree in Computer Science or related field

Tools

AWS

SSIS

GitHub CoPilot

Job description

Comcast Advertising seeks a data engineer to join a fully remote team. You will perform data engineering in an AWS cloud environment, handling S3, RDS, Lambda, and Secrets Manager, and you will work with SQL, ETL with Python/PySpark, and API development.

Responsibilities include building and maintaining data pipelines, using SAFe with CI/CD tooling, and collaborating across teams to ensure data quality and SLA compliance.