Data Platform Engineer | AWS, PySpark, Databricks

Comcast; West Chester (Chester County); Hybrid; USD 120,000 - 170,000; Full time

Job summary

Comcast is seeking a Data Engineer to join the Data Product Engineering team, managing and evolving a large enterprise Data Lake that supports critical datasets across the organization. You’ll build scalable data pipelines and cloud-native solutions using AWS, PySpark, and Databricks, enabling analytics and decision-making.

The role requires 5+ years of data engineering experience, strong distributed-systems knowledge, and collaboration across onshore and offshore teams.

Qualifications

• Bachelor's degree in CS, Engineering, or related field, or equivalent experience.
• 5+ years of Data Engineering or related experience.
• Strong hands-on AWS, PySpark, Databricks.
• Experience building large-scale ETL/ELT pipelines.
• Knowledge of distributed systems and data warehousing concepts.
• Experience with Apache Airflow/MWAA and Kubernetes.

Responsibilities

• Design, develop, and optimize scalable data pipelines for enterprise datasets.
• Build cloud-native data solutions using AWS, Databricks, and PySpark.
• Develop batch and streaming processing frameworks and integrate source systems.
• Leverage Kafka and Databricks streaming for near real-time data.
• Tune performance, automate workflows, and improve data platform operations.
• Provide production support and root-cause analysis for critical data workflows.
• Collaborate with Product, Data Governance, Analytics, and Engineering teams.
• Mentor junior engineers and contribute to team growth.
• Participate in architectural discussions for long-term data platform evolution.

Skills

AWS

PySpark

Databricks

Kubernetes

Airflow

Python

Data pipelines

Communication

Education

Bachelor's Degree

Tools

Databricks Platform

Kafka

Airflow/MWAA

Kubernetes

Snowflake

Job description

Comcast is seeking a Data Engineer to join the Data Product Engineering team, managing and evolving a large enterprise Data Lake that supports critical datasets across the organization. You’ll build scalable data pipelines and cloud-native solutions using AWS, PySpark, and Databricks, enabling analytics and decision-making.

The role requires 5+ years of data engineering experience, strong distributed-systems knowledge, and collaboration across onshore and offshore teams.