Senior Data Engineer at Devsu - Remote LATAM — Columbus
Traveler-Friendly Insight
Remote Flexibility & Timezone Fit: This role at Devsu is explicitly remote-friendly and targets LATAM-based engineers. The company serves US-based clients, which typically implies overlap with US Eastern or Central time zones (EST/CST). Expect some fixed meeting windows — likely mornings LATAM time — but the flexible schedule benefit suggests the role is largely async-compatible outside of those windows.
Visa & Location Considerations: The role is open to Colombia, Argentina, Peru, and broader Latin America. This is well-suited for nomads already based in LATAM. Popular nomad hubs within the allowed region include:
- Medellín, Colombia — Colombia offers a Digital Nomad Visa (Visa Nómada Digital) valid up to 2 years. Cost of living is very affordable, with comfortable apartments from ~$600–$900/month.
- Buenos Aires, Argentina — No formal nomad visa needed for many nationalities on tourist stays; the weak peso makes it one of the most affordable major cities globally for USD-earning nomads.
- Lima, Peru — Lower cost than Buenos Aires for most categories; tourist visas typically allow 90-day stays, extendable.
Perks for Nomads: The flexible PTO policy and remote culture are strong positives. Access to AI tools and continuous training means you can upskill from anywhere. No explicit mention of coworking stipends or home-office equipment budgets — worth confirming at the offer stage.
We are looking for a Senior Data Engineer with advanced, hands-on Databricks on Azure experience to design, build, modernise, and operate scalable data pipelines supporting Tax technology platforms. You will migrate and enhance existing Spark and Python workloads on Azure Databricks and build scalable ingestion and document-processing capabilities. We need someone who has owned production Databricks on Azure pipelines end to end, understands the wider system, surfaces assumptions and trade-offs, and proposes better approaches.
Responsibilities
- Design, build, and support scalable data pipelines using Python, Apache Spark, PySpark, and Databricks on Azure.
- Modernise and migrate legacy data processing workloads to secure, cloud-native platforms.
- Build and maintain batch data ingestion pipelines from structured and unstructured sources.
- Integrate data from REST APIs, SharePoint, document repositories, enterprise applications, and cloud platforms.
- Implement data quality, monitoring, observability, and operational controls.
- Optimise data workloads for performance, scalability, reliability, and cost efficiency.
- Develop document extraction, classification, metadata enrichment, and automation pipelines.
- Apply software engineering practices, including Git, CI/CD, automated testing, and code reviews.
- Build, deploy, troubleshoot, and maintain production ETL/ELT pipelines.
- Collaborate with architects, developers, tax subject matter experts, and platform teams.
- Analyse existing codebases and identify opportunities to improve maintainability, security, and reliability.
- Use AI-assisted development tools to build, review, test, and maintain data pipeline code.
Requirements — Must Have
- 5+ years of experience in data engineering.
- Strong Python development experience.
- Strong Apache Spark and PySpark experience.
- Advanced, hands-on Databricks on Azure experience in production (Delta Lake, Unity Catalogue, Workflows/Jobs, ADLS Gen2, Azure Data Factory).
- Strong SQL and data modelling skills.
- Experience building, testing, deploying, and troubleshooting production ETL/ELT pipelines.
- Experience with Git-based source control and CI/CD pipelines (e.g., Azure DevOps).
- Experience consuming REST APIs for data ingestion, including authentication, pagination, and failure handling.
- Experience writing automated tests for data pipelines.
- Strong understanding of data quality, reliability, and data engineering best practices.
- Strong problem-solving, communication, and collaboration skills, with sound judgement to analyse unfamiliar codebases, identify gaps and trade-offs, challenge requirements, and propose practical improvements.
Requirements — Nice to Have
- Experience modernising legacy data pipelines.
- Experience with document processing, intelligent document extraction, or unstructured data.
- Familiarity with AI-assisted development tools such as Codex, GitHub Copilot, or similar.
- Experience with streaming data pipelines or large-scale data repositories.
Benefits
- A stable, long-term contract with opportunities for career growth.
- Private health insurance.
- A remote-friendly culture that promotes work-life balance.
- Continuous training, mentorship, and learning programs to keep you at the forefront of the industry.
- Free access to AI training resources and state-of-the-art AI tools to elevate your daily work.
- A flexible Paid Time Off (PTO) policy as well as paid holiday days.
- Challenging, world-class software projects for clients in the US and LatAm.
- Collaboration with some of the most talented software engineers in Latin America and the US, in a diverse work environment.
Join Devsu and discover a workplace that values your growth, supports your well-being, and empowers you to make a global impact.
Frequently Asked Questions
Is this Senior Data Engineer role fully remote?
What is the contract type for this position?
What level of Databricks experience is required?
Is a salary range disclosed for this role?
Are AI tools provided or required for this role?
