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
📌 Senior Data Engineer (Perú)
🏢 Devsu
📍 Perú