Senior Data Engineer (Snowflake)
Summary
Fully remote (LatAm-only) senior data engineer role placed by staffing firm Motum with a US client: building scalable data pipelines, designing Snowflake warehouses and data models, developing ETL/ELT with Airflow, dbt, Python and SQL, and optimizing query and warehouse costs to prepare enterprise data for analytics and AI.
💻 Remote | LatAm - WE ARE EXCLUSIVELY CONSIDERING APPLICATIONS FROM INDIVIDUALS CURRENTLY RESIDING IN LATAM.
❗️ONLY ENGLISH RESUMES WILL BE CONSIDERED
🗣️ PLEASE NOTE THAT THIS ROLE REQUIRES ENGLISH PROFICIENCY (C1-C2 LEVEL)
About Motum
Motum connects experienced developers, engineers, and technical professionals with US companies building committed, long-term tech teams. Our roles are fully remote and full-time, designed for people who want real ownership, meaningful work, and the opportunity to grow inside US-based dynamic teams.
When you join Motum, you work full-time with one company, integrate directly into its team, and build a career with long-term impact. Ready to join us?
About the Client
Our client is a growing US-based technology company investing in a modern data platform. Its team brings data from multiple business systems into a dependable foundation for reporting, analytics, and AI applications. As data volumes and use cases grow, the company needs pipelines and models that teams can trust, maintain, and scale.
About the Role
We're looking for a hands-on Senior Data Engineer to build the data infrastructure behind that platform. You'll develop production ELT pipelines, design Snowflake models, and use dbt, Airflow, Python, and SQL to make enterprise data reliable and useful.
You'll work closely with analytics and AI teams, with ownership of data quality, pipeline performance, and Snowflake costs.
Responsibilities
- Build and maintain scalable pipelines that bring data from business systems into Snowflake.
- Design warehouse structures and data models that support reliable reporting, analytics, and AI use cases.
- Develop and maintain ELT transformations with dbt, using clear documentation, reusable models, and automated tests.
- Orchestrate workflows with Airflow; improve monitoring, alerts, and recovery when pipelines fail.
- Use Python and advanced SQL to transform data, troubleshoot issues, and improve pipeline performance.
- Put data quality checks and governance practices in place, including clear definitions, access controls, and traceable data flows.
- Optimize Snowflake queries, warehouse usage, and storage to improve performance while managing cost.
- Partner with analytics, product, and AI teams to turn data requirements into dependable production datasets.
Qualifications
- 6+ years of data engineering experience, including ownership of production pipelines and data models.
- 3+ years of hands-on Snowflake experience, including warehouse design, query optimization, and cost management.
- Strong advanced SQL and Python skills.
- Production experience with dbt and Airflow.
- Experience with AWS or Azure and a solid understanding of ETL/ELT patterns, data quality, and governance.
- Strong problem-solving skills, attention to detail, and the ability to explain data decisions to technical and nontechnical teammates.
- C1–C2 English proficiency and the ability to collaborate directly with a US-based team.
Nice to Have
- Experience with AI agent workflows, MCP, or LangGraph.
- A background in software engineering.
We Offer
- 100% remote — work from home
- 80 hours PTO + vacation days
- Ownership of a production data platform supporting analytics and AI
- Direct collaboration with US-based engineering, analytics, and AI teams
- Meaningful influence over data quality, performance, and how the platform scales
- A long-term opportunity to grow as part of the client's team