Senior Remote Full-Stack Engineer — Bi & Sql Specialist

BairesDev; Santa Fe Capital; Remote; ARS 900,000 - 1,400,000; Full time

Benefits offered by this job

Remote role

Async-friendly team

Job summary

BairesDev is seeking a Senior Data Engineer for a marketing-oriented role serving education and nonprofit clients. You will own data ingestion, data warehouse design, and the reporting pipelines feeding Looker Studio dashboards and automated reports.

The ideal candidate has 5+ years in data engineering within marketing or agencies, deep SQL and BigQuery experience, and proficiency in dbt or Dataform, Python, and CRM integrations to deliver scalable, observable data.

Qualifications

• 5+ years hands-on data engineering in marketing or agency settings.
• Strong SQL, BigQuery experience for transformation, modeling, and partitioning.
• Expertise with dbt or Dataform; modular, version-controlled pipelines.
• Python proficiency for API connections and automation.
• Experience with CRM data flows (Slate/Salesforce/HubSpot) and marketing metrics (ROAS, CPA, CAC).
• Familiarity with ETL tools (Adverity, Fivetran, Supermetrics) and Looker Studio optimization.
• Git and team collaboration; ability to manage multi-client data; clear communication.
• Education marketing domain experience is highly valued.

Responsibilities

• Own data ingestion and pipeline architecture from paid media and CRM into Adverity and warehouse.
• Maintain CRM connections (Slate, Salesforce, HubSpot) for clean data flows.
• Design and optimize Google BigQuery schemas, partitioning, and storage strategies.
• Develop modular, documented dbt/Dataform transformations with standardized metrics.
• Maintain CI/CD and data segregation for multi-client environments.
• Build Looker Studio dashboards and automated Google Sheets reports.
• Monitor data quality, resolve API breaks, and minimize latency.

Skills

5+ years data engineering

SQL

BigQuery

dbt

Dataform

Python

CRM integrations

Git

Marketing analytics

Looker Studio

Tools

Adverity

Fivetran

Supermetrics

dbt

Dataform

Job 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
• 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
• A pivotal, high‑visibility seat on a scaling Data & Analytics team, with real ownership over the agency's reporting infrastructure
• The chance to build the data backbone for an agency whose partners are education and nonprofit organizations working to build a better world
• A culture built around finding a better way, playing as a team of A‑players, and treating results as the engine rather than the goal
• Direct impact: the pipelines and models you build directly shape how partners see (and trust) their own performance data

Interview Process

• 1. Application Review (resume + a few questions)
• 2. Screening Call with Atomic HR
• 3. Hiring Team Interview (walkthrough of a pipeline or data model you've built)
• 4. Technical Assessment (a real-world data engineering case study)
• 5. Final Interview with company leadership