Senior Data Engineer - AI & Data Pipeline Architect

Comcast; New York (NY); On-site; USD 148,000 - 222,000; Full time

Job summary

FreeWheel, a Comcast company, is seeking a Senior Data Engineer to join our Audience & AI group in the Revenue Science team in New York. You will support data engineering efforts related to data analyses, AI, machine learning, optimization methods, and statistical model building, collaborating with engineering and product management staff to advance ad tech.

Responsibilities include building scalable data pipelines, ensuring data quality, and creating architectures that handle ingestion,

Qualifications

• Bachelor's degree in a technical field is required; Master’s or PhD is a plus.
• 7+ years of data engineering experience with large datasets.
• Experience with AWS, Databricks and Snowflake highly preferred; other platforms a plus.
• Knowledge of AI platforms, LLMs, and AI orchestration technologies is desirable.
• Experience with CI/CD, data pipelines and data quality is important.

Responsibilities

• Collaborate with cross-functional teams to define data-driven questions and run experiments.
• Engineer algorithms and automated processes for robust data integration and cleansing.
• Design data pipelines that ingest, transform and store data at scale.
• Build architectures for data ingestion, processing and storage.
• Ensure data quality and monitor pipelines; optimize compute/storage usage.
• Develop systems to detect security vulnerabilities and code issues.
• Work independently and across multiple projects.

Skills

Data Engineering

Machine Learning

Business Analytics

Collaboration

Data Science

Education

Bachelor's degree in technical field

Master’s or PhD a plus

Tools

AWS

Databricks

Snowflake

Kubernetes

Teradata

Datadog

Airflow

Job description

FreeWheel, a Comcast company, is seeking a Senior Data Engineer to join our Audience & AI group in the Revenue Science team in New York. You will support data engineering efforts related to data analyses, AI, machine learning, optimization methods, and statistical model building, collaborating with engineering and product management staff to advance ad tech.

Responsibilities include building scalable data pipelines, ensuring data quality, and creating architectures that handle ingestion,