Senior Principal, Data Product Engineering

Publicis Groupe · Chicago · $4,901–$4,919/month (stated in the posting)

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Click here to view how Epsilon transforms marketing with 1 View, 1 Vision, 1 Voice

Epsilon's transactional data products turn purchase and card-transaction signals into governed datasets that our audience, measurement, and client reporting teams build on. We're hiring a Senior Principal Engineer to own the quality and reliability of those datasets on our lakehouse platform.

This is a hands-on individual contributor role. You'll be in the pipelines and in the SQL, accountable for data that goes directly into client work - where correctness and timeliness are product requirements. It suits someone who is happiest close to the data, unbothered by a messy real-world domain, and treats doing the same fix twice as a bug.

• Empower with accountability: You own your data products end to end - ingestion through publication - and the engineering standards the rest of the team builds against.
• Innovate with purpose: You'd rather eliminate a class of problem than resolve an instance of it.
• Work together to win together: This role reports to the Senior Director, Data Product Engineering.

• Quality you can prove. Build the automated QC layer - completeness, distribution, referential integrity, anomaly detection - and turn the signal into a small number of alerts people actually trust.
• Reliability you own. Diagnose failures and discrepancies across large, high-cardinality data, and set freshness and correctness expectations you can demonstrate you're meeting.
• Toil that disappears. Replace recurring manual operations with automation and self-service tooling, and make compute proportional to what actually changed rather than to the size of the dataset.
• A platform that keeps improving. Evolve the Spark and SQL pipelines you own - tune refresh strategy and cost, retire the scaffolding that has outlived its purpose, and make each new source cheaper to onboard than the last.
• A higher bar. Set the standards other engineers follow - shared libraries, automated testing, code review, declarative deployment - and mentor the engineers and analysts around you.

What you'll bring with you

• 10+ years hands-on with production data, across data engineering, data operations, or data platform work
• Expert SQL, including performance tuning where a bad query plan costs hours and real money rather than seconds, plus strong production Python (PySpark preferred)
• A track record designing data quality, validation, monitoring, or reconciliation systems that measurably reduced defects or manual effort
• Real accountability for production batch pipelines, not only experience building them
• Large-scale distributed platforms (Databricks, Spark, or equivalent) and relational or MPP warehouses (Greenplum, Postgres, Snowflake, Redshift, or similar)
• Software engineering practice applied to data work: version control, code review, automated testing, CI/CD
• Comfort with messy, high-cardinality data - matching and deduplication included - and healthy skepticism toward data that looks too clean
• The ability to explain how an upstream change ripples into a downstream product to people who aren't engineers
• Bachelor's degree in a technical field, or equivalent practical experience

Why you might stand out from other talent

• Transaction, payments, card, retail POS, loyalty, or retail measurement data experience
• Delta Lake or equivalent, governed catalogs, incremental ingestion, and cluster or warehouse cost tuning
• Workflow orchestration at scale (Airflow, Databricks Jobs) and containerized deployment
• PII handling, pseudonymized identifiers, or work in regulated or clean-room environments
• Lightweight internal tooling (Flask or similar) for operational interfaces

When you join Epsilon, we’ll create something EPIC together. We’re a global leader in data and identity, with deep expertise in digital media, clean rooms, customer data platforms, loyalty and marketing services. Positioned at the center of Publicis Groupe, Epsilon helps brands deliver personalized experiences at scale and build lasting customer relationships by unlocking the full potential of data and identity. Epsilon operates in 30+ countries across EMEA, the Americas and APAC, with more than 8,000 employees.

Check out a few of these resources to learn more about what makes Epsilon so EPIC:

Our Culture: https://www.epsilon.com/us/about-us/our-culture-epsilon

Life at Epsilon: https://www.epsilon.com/us/about-us/epic-blog

Epsilon has five values that define our culture and guide us as we create value for our clients, our people and consumers. We seek candidates who align with our company values, demonstrate them and make them meaningful in their day-to-day work:

• Act with integrity. We are transparent and have the courage to do the right thing.
• Work together to win together. We believe collaboration is the catalyst that unlocks our full potential.
• Innovate with purpose. We shape the market with big ideas that drive big outcomes.
• Respect all voices. We embrace differences and foster a culture of connection and belonging.
• Empower with accountability. We trust each other to own and deliver on common goals.

Because You Matter

As an Epsilon employee, you deserve perks and benefits that put you, your family and your finances first. Our benefits encompass a wide range of offerings, including but not limited to:

• Time to recharge: Flexible time off (FTO), 14 paid holidays, paid sick time
• Family well-being: Parental/new child leave, childcare & elder care assistance, adoption assistance
• Extra perks: Comprehensive health coverage, 401(k), tuition assistance, commuter benefits, professional development, employee recognition, charitable donation matching, health coaching and counseling

Epsilon benefits are subject to eligibility requirements and other terms.

Epsilon is an Equal Opportunity Employer. Epsilon’s policy is not to discriminate against any applicant or employee based on actual or perceived race, age, sex or gender (including pregnancy), marital status, national origin, ancestry, citizenship status, mental or physical disability, religion, creed, color, sexual orientation, gender identity or expression (including transgender status), veteran status, genetic information or any other characteristic protected by applicable federal, state or local law. Epsilon also prohibits harassment of applicants and employees based on any of these protected categories. Epsilon will provide accommodations to applicants who need accommodations to complete the application process. Please reach out to LeaveofAbsence@epsilon.com to request an accommodation.

For San Francisco Bay and Los Angeles Areas: Epsilon will consider qualified applicants with criminal histories for employment in a manner consistent with the City of Los Angeles’ Fair Chance Initiative for Hiring Ordinance and San Francisco Police Code Sections 4901-4919, commonly referred to as the San Francisco Fair Chance Ordinance. Applicants with criminal histories are welcome to apply.

#LI-JC1

• Quality you can prove. Build the automated QC layer - completeness, distribution, referential integrity, anomaly detection - and turn the signal into a small number of alerts people actually trust.
• Reliability you own. Diagnose failures and discrepancies across large, high-cardinality data, and set freshness and correctness expectations you can demonstrate you're meeting.
• Toil that disappears. Replace recurring manual operations with automation and self-service tooling, and make compute proportional to what actually changed rather than to the size of the dataset.
• A platform that keeps improving. Evolve the Spark and SQL pipelines you own - tune refresh strategy and cost, retire the scaffolding that has outlived its purpose, and make each new source cheaper to onboard than the last.
• A higher bar. Set the standards other engineers follow - shared libraries, automated testing, code review, declarative deployment - and mentor the engineers and analysts around you.

What you'll bring with you

• 10+ years hands-on with production data, across data engineering, data operations, or data platform work
• Expert SQL, including performance tuning where a bad query plan costs hours and real money rather than seconds, plus strong production Python (PySpark preferred)
• A track record designing data quality, validation, monitoring, or reconciliation systems that measurably reduced defects or manual effort
• Real accountability for production batch pipelines, not only experience building them
• Large-scale distributed platforms (Databricks, Spark, or equivalent) and relational or MPP warehouses (Greenplum, Postgres, Snowflake, Redshift, or similar)
• Software engineering practice applied to data work: version control, code review, automated testing, CI/CD
• Comfort with messy, high-cardinality data - matching and deduplication included - and healthy skepticism toward data that looks too clean
• The ability to explain how an upstream change ripples into a downstream product to people who aren't engineers
• Bachelor's degree in a technical field, or equivalent practical experience

Why you might stand out from other talent

• Transaction, payments, card, retail POS, loyalty, or retail measurement data experience
• Delta Lake or equivalent, governed catalogs, incremental ingestion, and cluster or warehouse cost tuning
• Workflow orchestration at scale (Airflow, Databricks Jobs) and containerized deployment
• PII handling, pseudonymized identifiers, or work in regulated or clean-room environments
• Lightweight internal tooling (Flask or similar) for operational interfaces

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