Job Description

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.