Remote Senior Marketing Data Engineer (Bigquery/Python)
Senior data engineer for a performance marketing agency serving higher-ed and nonprofit clients: builds API pipelines from ad platforms and CRMs through Adverity into a BigQuery warehouse, models data with dbt/Dataform, and powers Looker Studio dashboards and automated Google Sheets reports. Core stack: Python, SQL, BigQuery, dbt, Adverity.
- Compensation
- Not disclosed
- Location
- La Pampa, Argentina
- Work setup
- Remote
- Seniority
- Senior
- Employment
- Full time
- Experience
- 5+ years
- Category
- Data engineering
- Posted
Skills
Must have
- 5+ years of hands-on data engineering experience, ideally in a marketing or agency environment
- Strong experience configuring datastreams, transformations, and destinations in Adverity or a comparable ETL platform (Fivetran, Supermetrics, Funnel)
- Intermediate to advanced SQL, with proven BigQuery experience in transformation, partitioning, and modeling
- Expertise in dbt or Dataform for modular, version-controlled, documented SQL transformation pipelines
- Python proficiency for custom API connections and pipeline automation
- Experience with CRM data flows and integrations (Slate, Salesforce, and/or HubSpot)
- Deep understanding of marketing metrics (ROAS, CPA, CAC) and paid platform schemas, with a track record of structuring data to optimize Looker Studio performance
- Proficiency with Git and collaborative development workflows
- Proven ability to manage multi-client data environments with strict data segregation
- Analytical, solution-driven mindset with strong communication skills for non-technical audiences
Nice to have
- Education marketing experience (traditional or online)
- Experience integrating AI-driven insights or ML models into marketing data pipelines for predictive analytics
- Familiarity using AI/LLM tools for performance forecasting, automated audience segmentation, or marketing workflows
- Experience connecting and maintaining APIs for generative AI platforms within a marketing data architecture
- Experience using AI/ML-driven anomaly detection to monitor pipelines and flag data quality issues
Full description
Data Engineer (Marketing-oriented) | Remote for Marketing Agency for Education
Our client is a fast-growing performance marketing agency specializing in mission-driven organizations across higher education and nonprofit sectors. Since launching in 2020, the agency has built a strong reputation for combining strategic thinking, creative execution, and data-driven marketing to help universities and organizations achieve measurable growth.
Company Overview
Our client is a fast-growing performance marketing agency specializing in mission-driven organizations across higher education and nonprofit sectors. Since launching in 2020, the agency has built a strong reputation for combining strategic thinking, creative execution, and data-driven marketing to help universities and organizations achieve measurable growth.
Your Role
The Senior Data Engineer sits at the center of the agency's Data and Analytics function, connecting every paid media platform and CRM the agency touches into a single, reliable source of truth. You'll own the full path data takes: from a client's ad accounts and CRM, through Adverity, into a BigQuery warehouse, through modular dbt/Dataform transformations, and out to the Looker Studio dashboards and automated Google Sheets reports the team and its partners rely on daily. Reporting to the Data and Analytics Manager, you're joining at a pivotal moment — the agency is scaling its roster of education and nonprofit partners, and this role is instrumental in evolving the automated reporting suite that makes that growth possible without sacrificing data quality or client trust.
You'll
- Own data ingestion & pipeline architecture — connect and maintain API pipelines from paid media platforms (Meta, Google Ads, LinkedIn, TikTok, programmatic) into Adverity, build custom Python connectors for anything not natively supported, and architect scalable pipelines from source system through to dashboard
- Own CRM integration — build and maintain reliable CRM data connections (Slate, Salesforce, HubSpot) so lead and enrollment data flows cleanly into the warehouse
- Own the data warehouse — route, optimize, and store raw and processed data in Google BigQuery; design efficient schemas for complex, multi-source marketing data (granularity, normalization, slowly changing dimensions); manage partitioning, clustering, and storage strategy to control query cost and performance
- Own transformation & mapping — build SQL schemas that map, blend, and organize multi-channel data accurately for each client, in modular, version-controlled, documented dbt or Dataform pipelines, with standardized naming conventions and metric definitions across platforms and clients
- Own CI/CD & data segregation — maintain CI/CD pipelines (GitHub Actions, automated testing) for robust, version-controlled releases, and enforce strict data segregation across multi-client environments