Remote Data Engineer For Cost Attribution & Financial Modeling

Agileengine, Llc.; Santa Fe Capital; Remote; ARS 182,437,000 - 273,656,000; Full time

Benefits offered by this job

Remote work

Competitive compensation

Job summary

Agileengine, Llc. seeks a Senior Data Engineer (Marketing-oriented) to own end-to-end data pipelines from ads to warehouse and dashboards. You will integrate Meta, Google Ads, LinkedIn, TikTok, and CRM data into Adverity, build dbt/Dataform transformations, and feed Looker Studio reports.

Reporting to the Data and Analytics Manager, you will design scalable BigQuery schemas, enforce data quality, and enable automated reporting for education and nonprofit clients.

Qualifications

• 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, managing 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).
• A deep understanding of marketing metrics (ROAS, CPA, CAC) and paid platform schemas, with a proven track record of structuring data to optimize Looker Studio performance.
• Proficiency with Git and collaborative development workflows, and proven ability to manage multi-client data environments with strict data segregation.

Responsibilities

• Own data ingestion & pipeline architecture — connect and maintain API pipelines from paid media platforms into Adverity, build custom Python connectors, and architect scalable pipelines.
• Own CRM integration— build and maintain reliable CRM data connections so lead and enrollment data flows into the warehouse.
• Own the data warehouse — route, optimize, and store raw and processed data in Google BigQuery; design schemas for multi-source marketing data; manage partitioning, clustering, and storage strategy.
• Own transformation & mapping— build SQL schemas that map, blend, and organize multi-channel data in modular dbt/Dataform pipelines.
• Own CI/CD & data segregation— maintain CI/CD pipelines (GitHub Actions, automated testing) for robust, version-controlled releases with strict data segregation.
• Enable the reporting layer— create clean data views for Looker Studio dashboards and Google Sheets reports; translate reporting requirements into warehouse models.
• Drive data quality— monitor pipelines, resolve API breaks, implement validation and testing, flag data quality risks.

Skills

Data engineering

ETL pipelines

SQL

BigQuery

dbt/Dataform

Python

CRM integration

Marketing metrics

Git

Education marketing

Tools

Adverity

Looker Studio

Job description

BigQuery

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

• Enable the reporting layer — create clean, performant data views built specifically for fast Looker Studio dashboards and automated Google Sheets reports, and partner with the Data and Analytics Manager and client teams to translate reporting requirements into warehouse models

• Drive data quality — monitor pipeline health, resolve API breaks, minimize latency, implement validation frameworks and automated testing, troubleshoot discrepancies to root cause across source/warehouse/BI layers, and proactively flag data quality risks to leadership

You Bring:

• 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, managing 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)

• A deep understanding of marketing metrics (ROAS, CPA, CAC) and paid platform schemas, with a proven track record of structuring data to optimize Looker Studio performance

• Proficiency with Git and collaborative development workflows, and proven ability to manage multi-client data environments with strict data segregation

• An analytical, solution-driven mindset with a growth orientation, and strong communication skills that turn complex data workflows into clear narratives for non-technical audiences — education marketing experience (traditional or online) is especially valued

Bonus Points:

• Experience integrating AI-driven insights or machine learning models into marketing data pipelines to sharpen predictive analytics and data utility

• Familiarity using AI or LLM tools to optimize performance forecasting, automated audience segmentation, or marketing workflows

• Experience connecting, managing, and maintaining APIs for generative AI platforms within a marketing data architecture

• Experience using AI/ML-driven anomaly detection to monitor pipelines and proactively flag data quality issues

What’s Offered:

• Remote role with the flexibility that comes with a distributed, async-friendly team

• Competitive compensation based on experience and location