Data Engineer Intern: Build Pipelines & Analytics

Optimum Media

New York (NY)

On-site

USD 41,328,000 - 55,104,000

Part time

6 days ago
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Job summary

Optimum Media seeks a Data Engineer Intern to support data pipelines, data infrastructure, and analytical solutions. You will work with data engineers and analytics teams to ingest, process, and manage data across systems, and help improve data quality and pipeline reliability.

This role offers exposure to cloud data platforms and modern data tooling, with hands-on learning and collaboration across engineering and analytics teams in a dynamic media environment.

Qualifications

  • Bachelor's or Master's in Data Science, CS, or related field per the posting.
  • Graduate degree preferred; 1–2 years related experience helpful.
  • Strong SQL and Python skills with data warehousing exposure.
  • Experience with cloud data platforms like BigQuery/Redshift/Snowflake a plus.
  • Familiarity with ETL/ELT concepts and data pipelines.

Responsibilities

  • Support development and maintenance of data pipelines and ETL/ELT processes.
  • Collaborate with data engineers and analysts on data structures and quality.
  • Work with BigQuery, Snowflake, Databricks to enable reporting needs.
  • Document data processes and architecture following best practices.
  • Assist in data ingestion, validation, and workflow automation.

Skills

SQL
Python
Data warehousing
ETL/ELT
Data analysis
Linux/Bash scripting
Git/GitHub

Education

Bachelor's or Master's in Data Science/Computer Science

Tools

Google BigQuery
Snowflake
Databricks
AWS Redshift

Job description

Optimum Media seeks a Data Engineer Intern to support data pipelines, data infrastructure, and analytical solutions. You will work with data engineers and analytics teams to ingest, process, and manage data across systems, and help improve data quality and pipeline reliability.

This role offers exposure to cloud data platforms and modern data tooling, with hands-on learning and collaboration across engineering and analytics teams in a dynamic media environment.

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