Data Engineer: AI-Driven Data Pipelines & ML

Comcast

Philadelphia (Philadelphia County)

On-site

USD 109,000 - 163,000

Full time

5 days ago
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Job summary

Comcast, a Fortune 30 global media and technology company, is seeking a data engineer to design, build, and optimize large-scale data pipelines and ML workflows. You will collaborate with network engineering, product, operations, software development and data science teams to deliver scalable data applications on AWS, Databricks, and Spark.

You will implement ETL/ELT processes, data quality checks, governance, and monitoring, while advancing AI-enabled analytics and model deployment in

Qualifications

  • Strong proficiency in SQL and Python with data engineering and analytics experience.
  • Experience building production data applications on cloud platforms.
  • Knowledge of ETL/ELT, data quality, governance, and monitoring.
  • Familiarity with ML workflows and AI-enabled analytics.
  • Ability to collaborate across technical and business teams.

Responsibilities

  • Design, develop, test, and support scalable data applications and data pipelines.
  • Build and optimize ELT/ETL processes across batch and streaming data.
  • Develop data-quality checks, lineage, and monitoring automation.
  • Develop ML models and productionize them into data workflows.
  • Document pipelines, architecture, and deployment procedures.

Skills

SQL
Python
Data engineering
Data analytics
Problem solving
Communication

Education

Bachelor's Degree

Tools

AWS
Databricks
Spark
Airflow
Tableau/Power BI

Job description

Comcast, a Fortune 30 global media and technology company, is seeking a data engineer to design, build, and optimize large-scale data pipelines and ML workflows. You will collaborate with network engineering, product, operations, software development and data science teams to deliver scalable data applications on AWS, Databricks, and Spark.

You will implement ETL/ELT processes, data quality checks, governance, and monitoring, while advancing AI-enabled analytics and model deployment in

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