Product Data Engineer

Comcast

Confirmed live yesterday High trust

Quick summary

Work type
On-site
Location
West Chester, PA
Posted
6 days ago
Freshness
Confirmed live yesterday

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Salary context

How this pay compares to similar roles

Similar $177k
$131k most similar roles pay here $226k

This listing doesn't post a salary. Most similar roles pay $139,914–$213,375.

Based on 240 similar postings.

Employer

About Comcast

Comcast is an American telecommunications and media conglomerate, providing cable TV, internet, and phone services under the Xfinity brand, and owning NBCUniversal.

Comcast currently has 84 open roles on FindRole.

Listed pay typically runs $137,369–$206,053 across 58 roles with salary data.

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At a glance

TL;DR · Product Data Engineer

The Product Data Engineer joins the Data Product Engineering team to manage and evolve an enterprise Data Lake supporting critical workforce, billing, and interaction datasets. This role involves designing, developing, and optimizing scalable data pipelines and cloud-native solutions to support high-volume data processing for analytics and reporting. The engineer will build batch and streaming data processing frameworks, perform performance tuning, and provide production support for distributed systems handling tens of terabytes of data. Key technologies include AWS, Databricks, PySpark, Kafka, Kubernetes, and MWAA (Managed Workflows for Apache Airflow). Candidates must possess proficiency in Python development and experience with ETL/ELT pipelines and modern data architectures. The role focuses on solving complex problems related to large-scale interaction and customer engagement data while ensuring high quality, reliability, and scalability across the enterprise platform.

What you'll do

  • Design, develop, and optimize scalable data pipelines for workforce, billing, and interaction datasets.
  • Build and enhance cloud-native data solutions using AWS, Databricks, and PySpark.
  • Develop batch and streaming data processing frameworks to integrate source systems into modern architectures.
  • Use Kafka and Databricks streaming solutions to ingest and process high-volume data in near real-time.
  • Orchestrate and manage complex data workflows using MWAA (Managed Workflows for Apache Airflow).
  • Provide production support, troubleshooting, and root-cause analysis for critical data workflows.
  • Drive performance tuning, automation initiatives, and operational improvements across the data platform.
  • Mentor junior engineers and provide technical guidance to team members.

What we're looking for

  • Bachelor's degree in Computer Science, Engineering, Information Systems, or a related field, or equivalent practical experience.
  • 5+ years of experience in Data Engineering, Data Platform Engineering, or related disciplines.
  • Strong hands-on experience with AWS, PySpark, and Databricks.
  • Experience building and maintaining large-scale ETL/ELT pipelines and distributed systems for high-volume data processing.
  • Proficiency in Python development within data engineering environments.
  • Experience orchestrating workflows using Apache Airflow or MWAA.
  • Knowledge of Kubernetes fundamentals including pod lifecycle and job orchestration.

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