Data Engineer (Marketing Intelligence)

Job Title: Data Engineer (Marketing Intelligence) Location:

Remote Commitment:

(25–30 hours/week) Experience:

3+ Years

Role Overview We are looking for a specialized

Data Engineer

to bridge the gap between fragmented marketing platforms and our central data warehouse. This is

not

a marketing or campaign management role. This is a technical engineering role focused on the extraction, transformation, and loading (ETL/ELT) of complex marketing datasets. The ideal candidate has spent significant time \"under the hood\" of GA4, Meta, and TikTok APIs, ensuring data integrity for high-stakes analytics.

Key Responsibilities Pipeline Development:

Design and maintain robust data pipelines to ingest data from

GA4 (BigQuery Export), Meta Ads API, TikTok Ads, and Google Tag Manager . Data Modeling:

Transform raw marketing JSON/API outputs into clean, queryable schemas (Star/Snowflake) within the Data Warehouse. Schema Mapping:

Resolve data discrepancies between platforms (e.g., reconciling click-through data from Meta vs. session data in GA4). API Management:

Handle authentication (OAuth), rate-limiting, and pagination for various marketing vendor APIs. Quality Assurance:

Monitor pipeline health to ensure marketing dashboards reflect real-time accuracy.

Technical Requirements Experience:

3+ years in Data Engineering with at least

two dedicated Marketing Analytics projects

in your portfolio. Stack:

Proficiency in Python or Node.js for API scripting and advanced SQL for data transformation. Marketing Tech Proficiency: GA4:

Deep understanding of the BigQuery export schema. GTM:

Knowledge of how server-side tagging impacts data collection. Social APIs:

Hands-on experience with Meta Graph API and TikTok Ads API. Cloud/Warehousing:

Experience with Snowflake, BigQuery, or Redshift. ETL Tools:

Familiarity with Fivetran, Airbyte, or dbt is a significant plus.