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Data Engineer – MVA Inference & Audience Development

Ravlco — Kazakhstan · Posted ~1 month ago

Full-time Remote

Skills

SQL Data Modeling Python Cloud Platforms Data Warehousing Data Governance Aggregated Geospatial Data ETL/ELT Pipelines AWS GCP Azure Snowflake BigQuery Redshift

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Summary ✨ AI‑Generated

Join a global remote data engineering team building privacy-safe infrastructure for audience intelligence. You will develop reliable ETL/ELT pipelines, reusable inference layers, audit-ready segmentation workflows, governance controls, and aggregated geospatial data solutions while collaborating with growth and compliance stakeholders.

Highlights

Fully remote global role focused on privacy-safe data infrastructure, reusable inference systems, governed segmentation workflows, and scalable data pipelines. The position offers exposure to cloud platforms, geospatial analytics, data governance, and cross-functional collaboration.

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 pipelinesDevelop reusable inference layersCreate audit-ready segmentation workflowsImplement governance controls (lineage, validation, logging)Perform geospatial aggregation (ZIP, county, corridor)Collaborate with Growth and Compliance teams Success (60–90 Days) Reliable, monitored pipelinesGoverned inference layer libraryStandardized segmentation workflowsImproved audience performance Required Qualifications Strong SQL and data modellingPython proficiencyCloud platforms (AWS, GCP, Azure)Data warehouses (Snowflake, BigQuery, Redshift)Data governance experienceAggregated geospatial data experience Compliance Expectations Understand inference vs. knowledgeUse only aggregated historical data (45+ days old)No real-time or individual-level data usageVendor diligence and audit logging Nice to Have Marketing segmentation experiencePrivacy 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.