Senior Data Engineer (Databricks on Azure)
At a glance
Senior Data Engineering role at Devsu. Remote, Colombia · full-time.
Pay not stated Data Engineer salary
dataroles summary, based on the employer's posting.
What you'll do
- Build and run Python, Spark and PySpark pipelines on Azure Databricks, including production ETL and ELT workloads
- Move older processing workloads to secure cloud platforms and improve their maintainability, security and reliability
- Ingest structured and unstructured data from REST APIs, SharePoint, document stores and enterprise systems
- Add data quality checks, monitoring and operational controls, then tune pipelines for speed, scale and cost
- Create document extraction and classification flows, using metadata enrichment and automation where needed
What you bring
- At least five years in data engineering, with strong Python, Spark and PySpark skills
- Hands-on production experience with Azure Databricks, including Delta Lake, Unity Catalogue and related Azure services
- You can model data in SQL and build, test, deploy and troubleshoot production ETL or ELT pipelines
- You have used Git and CI/CD, written automated pipeline tests, and handled REST API authentication, pagination and failures
Who this fits
This senior role suits someone who has owned Azure Databricks pipelines in production and can assess unfamiliar code, weigh trade-offs and suggest practical improvements. The position is remote in Colombia and involves working with architects, developers, tax specialists and platform teams.
From the employer
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.
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. Continuous Training. Private Health insurance. Flexible schedule. Work with some of the most talented software engineers in Latin America and the US, doing challenging work and world-class software for clients in the US and around the world.
At Devsu, we believe in creating an environment where you can thrive both personally and professionally. By joining our team, you’ll enjoy:
• 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.
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