Senior Principal Data Platform Engineer

Publicis Groupe; Chicago (IL); On-site; USD 133,000 - 247,000; Full time

Benefits offered by this job

Flexible time off

Parental leave

Health coverage

401(k)

Tuition assistance

Commuter benefits

Professional development

Employee recognition

Donation matching

Health coaching

Job summary

Epsilon in Chicago, IL, is hiring a Senior Principal Engineer to own the quality and reliability of datasets on our lakehouse platform. This hands-on role sits in pipelines and SQL, accountable for data that feeds client work and requires timely, correct results.

You will evolve Spark and SQL pipelines, implement automated QC, and mentor engineers and analysts. Strong Databricks/Spark experience and a technical degree are expected.

Qualifications

• 10+ years hands-on with production data in data engineering, operations, or platform work.
• Expert SQL with performance tuning; strong production Python (PySpark preferred).
• Track record in data quality, validation, monitoring, or reconciliation systems.

Responsibilities

• Build automated QC layer for completeness, distribution, referential integrity, and anomaly detection.
• Own reliability of large, high-cardinality data pipelines across Spark and SQL.
• Automate recurring operations and enable self-service tooling to reduce toil.
• Evolve pipelines, optimize refresh strategy and cost, and onboard new sources cost-effectively.
• Set engineering standards and mentor other engineers and analysts.

Skills

Advanced SQL

PySpark

Python

Data quality

Data pipelines

Databricks

Spark

CI/CD

Version control

Communication

Education

Bachelor's degree in a technical field

Tools

Databricks

Spark

Greenplum

Postgres

Snowflake

Redshift

Job description

Epsilon in Chicago, IL, is hiring a Senior Principal Engineer to own the quality and reliability of datasets on our lakehouse platform. This hands-on role sits in pipelines and SQL, accountable for data that feeds client work and requires timely, correct results.

You will evolve Spark and SQL pipelines, implement automated QC, and mentor engineers and analysts. Strong Databricks/Spark experience and a technical degree are expected.