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

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.