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 Big Query 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, Linked In, Tik Tok, 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, Hub Spot) so lead and enrollment data flows cleanly into the warehouse
Own the data warehouse — route, optimize, and store raw and processed data in Google Big Query; 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 (Git Hub 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 Big Query 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 Hub Spot)
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:
Application Review (resume + a few questions)
Screening Call with Atomic HR
Hiring Team Interview (walkthrough of a pipeline or data model you've built)
Technical Assessment (a real‑world data engineering case study)
Final Interview with company leadership
Buenos Aires, Buenos Aires, Argentina Full timeRUtilizes software engineering principles to deploy and maintain fully automated data transformation pipelines that combine a large variety of storage and computation technologies to handle a distribution of data types and volumes in support of data architecture design. Job DescriptionGBS Chevron Integral Business Services (GBS), located in Buenos Aires (Puerto Madero), Argentina, is accepting applications for the position of Data Engineer. Successful candidates will join the IT Organization, which is part of a multifunction service and technical center with a workforce of more than 1800 employees that deliver business services and solutions to the corporation across the globe.
Utilizes software engineering principles to deploy and maintain fully automated data transformation pipelines that combine a large variety of storage and computation technologies to handle a distribution of data types and volumes in support of data architecture design. Responsibilities include:+ Understand business use of data and stakeholder requirements to support work processes and strategic business objectives+ Leverage data, software engineering, and data science techniques to create business value through data accessibility. Includes data ingestion, data preparation and analytics processing.+ Identify, acquire, cleanse & prepare, store data and develop data products aligned with defined architecture patterns+ Responsible for normalizing and ingesting data from multiple sources.+ Enable data scientists, making data available for advanced analytics models, and contributing to models.+ Work with ML Engineer to scale and deploy solution including model, documentation, training, integration+ Contributing to the inner source development of foundational tools, and/or the deployment of technical services. Required Qualifications:+ BS in Computer Science, Management Information Systems, Computer Engineer or related fields or equivalent experience.+ +5 years in Data Engineer Role+ Knowledge and/or experience with: data acquisition, preparation and validation; data movement and transformation; analytics solution architecture; big data computing; cloud computing, core data architecture; information security technologies and software engineering using technologies such as: Azure Data Factory (ETL), Databricks, Dev Ops, CI/CD Pipeline Deployment, Python, Java, Ansible, Azure SQL, Azure Synapse, GIT, ADO, Azure Data Lake, Azure Analysis Services, Logic Apps, Microsoft Data Flows, Kimball Data Warehousing Methodology+ Analytical thinking, Consulting, Critical Thinking Relocation Options: Relocation may be considered. International Considerations: Expatriate assignments will not be considered Chevron regrets that it is unable to sponsor employment Visas or consider individuals on time‑limited Visa status for this position Chevron participates in E‑Verify in certain locations as required by law. Chevron Corporation is one of the world’s leading integrated energy companies. Through its subsidiaries that conduct business worldwide, the company is involved in virtually every facet of the energy industry. Chevron explores for, produces and transports crude oil and natural gas; refines, markets and distributes transportation fuels and lubricants; manufactures and sells petrochemicals and additives; generates power; and develops and deploys technologies that enhance business value in every aspect of the company’s operations. Chevron is based in Houston, Texas. More information about Chevron is available at . Chevron is an Equal Opportunity / affirmativa... Qualified applicants will receive consideration for employment without regard ...
We do this by finding value‑add and opportunistic investments offering solid returns to our investors.
Providing an opportunity ...
In 2021, we were listed as the 5th fastest growing real estate company in the US ...
We are members of the Inc. 5000 fastest‑growing private companies in America and in 2023 we were #13 ...
5000 fastest‑growing private companies in America and in 2023 we were #13 ... Mission As the Data Engineer you will design, build, and optimize scalable data infrastructure that powers marketing, business intelligence, and strategic decision‑making across the organization.
You will develop reliable data pipelines, integrate third‑party platforms, and transform raw data into actionable insights through automation, analytics, and visualization.
Working closely with cross‑functional teams, you will ensure data is accurate, accessible, and optimized for performance while continuously identifying opportunities to improve processes and capabilities.
This role combines technical expertise, innovation, and collaboration to deliver high‑quality data solutions that support business growth.
Outcomes Data Pipeline Development – Design, build,



and optimize end‑to‑end data pipelines from ingestion through transformation and visualization, delivering scalable, reliable solutions that achieve 99%+ successful pipeline execution.
Platform Integrations – Integrate third‑party tools and platforms, including CRMs, Mar Tech platforms, and custom applications, using APIs, webhooks, and modern integration methods while maintaining reliable data synchronization.
ETL/ELT Optimization – Develop, improve, and maintain ETL/ELT workflows that ensure clean, accurate, and scalable data processing while minimizing failures and manual intervention.
Data Analysis & Insights – Conduct in‑depth data and trend analysis to deliver actionable insights that support data‑driven marketing strategies and business decision‑making.
Cross‑Functional Collaboration – Partner with marketing, data, and business intelligence teams to deliver technical solutions that align with business objectives while meeting project timelines and stakeholder expectations.
Data Warehouse Performance – Optimize data storage and retrieval performance across platforms such as Big Query, Snowflake, or Azure Synapse to improve query efficiency, scalability, and data accessibility.
Business Intelligence Reporting – Create and maintain Power BI and other business intelligence dashboards that provide accurate, timely reporting and actionable insights for stakeholders.
Continuous Improvement & Ownership – Continuously identify opportunities to improve workflows, reporting, and data capabilities while independently managing priorities, communicating progress transparently, and consistently delivering high‑quality solutions Qualifications 2+ years of experience as a Data Engineer, Mar Tech Developer, or similar role.
Proficiency in Python and SQL for data engineering, automation, and analytics.
Experience designing, building, and optimizing end‑to‑end ETL/ELT data pipelines.
Experience developing and maintaining REST APIs, webhooks, and third‑party system integrations.
Knowledge of data modeling, data architecture, and data integration best practices.
Experience working with Google Big Query, Data Lake environments, or similar cloud‑based data platforms.
Experience creating reports and dashboards using Power BI, Tableau, or similar business intelligence tools.
Experience with Snowflake, Azure Synapse, or other cloud‑based data warehouse platforms preferred.
Experience automating workflows using scripting tools, Zapier, or custom automation solutions preferred.
Experience developing chatbot, Generative AI, or machine learning solutions preferred.
Experience supporting marketing technology (Mar Tech), CRM, or business intelligence ecosystems preferred.
Ability to work full‑time and maintain significant overlap with U.S. business hours, including evening or overnight schedules as needed.
Remote Work Requirements Dedicated home office or professional remote work environment.
Reliable high‑speed ...
Agile Engine is an Inc. 5000 company that creates award‑winning software for Fortune 500 brands and trailblazing startups across 17+ industries. We rank among the leaders in areas like application development and AI/ML, and our people‑first culture has earned us multiple Best Place to Work awards.
Why join us? If you’re looking for a place to grow, make an impact, and work with people who care, we’d love to meet you!
About the Role We are looking for a Mid‑level Data Engineer to build and maintain dbt pipelines and Snowflake data marts behind customer‑facing reporting, spend analytics, and AI features.
The mandatory requirements ...
What You Will Do
Build and maintain the dbt pipelines, data marts, and warehouse models that serve in‑app reporting, spend analytics, AI features, treating them as production systems.
Translate complicated procurement business logic into maintainable, well‑tested pipeline code, and notice when a model is valid‑looking but wrong.
Build models within our data mart architecture, following the chapter’s conventions for grain, conformed dimensions, and incremental patterns, and propose improvements when you find them.
Contribute to and help buildout the semantic layer that our internal MCP servers and AI agents query, so that metrics and dimensions are defined once and answered consistently.
Maintain the boundary between PII and agent/reporting‑safe data.
Build and maintain the FastAPI services that expose reporting marts to customers.
Build and maintain ingestion pipelines (Airbyte, One Schema, S3) into the warehouse, and support our Forward Deployed Engineering function in bringing customer data into our systems.
Implement data quality checks: freshness, schema and reconciliation tests, and alerting, so problems surface before customers find them.
Implement metric definitions faithfully, and flag conflicting or ambiguous definitions to the chapter rather than guessing.
Keep documentation and lineage current so that humans and AI agents can both find and trust what’s in the warehouse.
Tune Snowflake performance and cost within the models you build.
Use agentic coding tools in your daily work, within the guardrails (tests, conventions, review patterns) the team maintains, and understand why those guardrails exist.
Share what you learn through code review and team discussion.
Communicate clearly with engineering, product, and customer‑facing teams about what the data means and what it can and can’t do.
MUST HAVES
3+ years in analytics engineering, data engineering, or a closely related role, including hands‑on work on production data pipelines that other systems or customers depended on.
Solid dbt experience: modeling, tests, macros, and incremental models.
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📌 Data Engineer (Marketing-Oriented) | Remote For Marketing Agency For Education (Córdoba)
🏢 Atomic Hr
📍 Córdoba