Data Engineer – MVA Inference & Audience Development (Remote)

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. The role focuses on using aggregated, historical signals and never real‑time or individual‑level data.

Key responsibilities

• Build and maintain ETL/ELT pipelines.
• Develop reusable inference layers.
• Create audit‑ready segmentation workflows.
• Implement governance controls such as lineage, validation, and logging.
• Perform geospatial aggregation at ZIP, county, and corridor levels.
• Collaborate with Growth and Compliance teams.

Required profile

• Strong SQL and data modelling expertise.
• Proficiency in Python.
• Experience with cloud platforms (AWS, GCP, Azure).
• Experience with data warehouses (Snowflake, BigQuery, Redshift).
• Background in data governance and aggregated geospatial data.
• Understanding of inference vs. knowledge and strict use of aggregated historical data (45+ days old).
• Commitment to privacy‑safe practices, avoiding real‑time or individual‑level data.
• Vendor diligence and audit‑logging experience.

Required skills

• SQL
• Python
• AWS
• GCP
• Azure
• Snowflake
• BigQuery
• Redshift
• dbt
• Airflow
• Dagster
• Spark

What we offer

• Competitive compensation based on experience, skills, and location.
• Fully remote work with a global team.
• Opportunity to shape privacy‑first data infrastructure for marketing intelligence.