About The Role

We are hiring a Data Engineer to build and maintain compliant, privacy-safe data infrastructure that powers audience development and marketing intelligence systems. This role ensures all data pipelines operate using aggregated, historical signals—never real-time incident or individual-level data.

Key Responsibilities

Build and maintain ETL/ELT pipelines
Develop reusable inference layers
Create audit-ready segmentation workflows
Implement governance controls (lineage, validation, logging)
Perform geospatial aggregation (ZIP, county, corridor)
Collaborate with Growth and Compliance teams

Success (60–90 Days)

Reliable, monitored pipelines
Governed inference layer library
Standardized segmentation workflows
Improved audience performance

Required Qualifications

Strong SQL and data modelling
Python proficiency
Cloud platforms (AWS, GCP, Azure)
Data warehouses (Snowflake, BigQuery, Redshift)
Data governance experience
Aggregated geospatial data experience

Compliance Expectations

Understand inference vs. knowledge
Use only aggregated historical data (45+ days old)
No real-time or individual-level data usage
Vendor diligence and audit logging

Nice to Have

Marketing segmentation experience
Privacy frameworks (CCPA, GDPR, TCPA)
dbt, Airflow, Dagster, Spark

Compensation

Compensation is based on experience, skills, and location and will be competitive within the global market.

Data Engineer – MVA Inference & Audience Development (Remote, Global)

Data Engineer – MVA Inference & Audience Development (Remote, Global)

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