Principal Data Engineer - Remote, Scalable ELT Pipelines

Jobot; Chicago (IL); Remote; USD 170,000 - 205,000; Full time

Benefits offered by this job

Annual performance bonus

Medical, dental, vision coverage

401k with 4% match

Unlimited PTO

Remote flexibility

Competitive compensation packages

Job summary

Jobot is hiring a highly skilled Principal Data Engineer to join our Data & Analytics team in a fully remote, US-wide position. You’ll design, build, and scale data pipelines and architectures to power enterprise analytics and data products.

The ideal candidate has deep experience with ELT development, dimensional modeling, and modern cloud data platforms, with ownership across the data lifecycle—from ingestion to curated data marts.

Qualifications

• Bachelor’s degree in Computer Science, Engineering, or equivalent experience.
• 5+ years of experience building ELT pipelines in a Data Warehouse environment.
• Strong experience with dimensional data modeling (Kimball, Data Vault, Medallion).
• Hands‑on expertise with dbt, Airflow or Dagster.
• Strong experience with Snowflake or similar cloud data warehouses, distributed data systems, Kubernetes environments.
• Deep understanding of Append‑only data modeling & point‑in‑time data structures, column‑oriented / analytical SQL modeling.
• Strong proficiency in Python, SQL.
• Experience implementing Test‑driven development (TDD) for data pipelines, Git‑based workflows and CI/CD best practices.

Responsibilities

• Design, build, and scale modern data pipelines and architectures to support analytics and data products.
• Own data lifecycle from ingestion through curated data marts, focusing on performance and data quality.
• Contribute to data mesh or data platform architecture discussions and implementation.

Job description

Jobot is hiring a highly skilled Principal Data Engineer to join our Data & Analytics team in a fully remote, US-wide position. You’ll design, build, and scale data pipelines and architectures to power enterprise analytics and data products.

The ideal candidate has deep experience with ELT development, dimensional modeling, and modern cloud data platforms, with ownership across the data lifecycle—from ingestion to curated data marts.