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Senior Databricks Engineer

  • AgileEngine
  • Bucaramanga, Colombia, Colombia
  • $100,000 – $140,000

AgileEngine 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 Senior Data Engineer to build batch and streaming pipelines on Databricks using PySpark and Delta Lake. This person migrates legacy data warehouse and ETL workloads onto a governed Lakehouse, modeling a medallion architecture that powers analytics and AI use cases. Strong SQL, Python, and experience with Unity Catalog governance round out the role.

WHAT YOU WILL DO

  • Design, build, and operate batch and streaming data pipelines on Databricks using PySpark, Delta Lake, and Databricks Workflows.

  • Model and maintain a medallion (bronze/silver/gold) architecture serving analytics, reporting, and machine learning consumers.

  • Migrate legacy ETL and data warehouse workloads onto the Lakehouse with validated data parity and minimal business disruption.

  • Use Claude or GitHub Copilot as a development accelerator, generating code scaffolding, writing and reviewing tests, creating documentation, and prototyping solutions.

  • Write clean, well-tested Python and SQL; maintain high standards through code review and documentation.

  • Optimize Spark jobs and Delta tables for performance and cost, including partitioning, clustering, caching, and cluster sizing.

  • Implement data quality, lineage, and governance controls using Unity Catalog and automated validation checks.

  • Debug, troubleshoot, and resolve pipeline failures, data defects, and production incidents.

  • Collaborate with DevOps, platform, and analytics engineers on observability, security, and compliance best practices.

MUST HAVES

3+ years of professional experience in data engineering , featuring direct expertise with Apache Spark and cloud-based data architectures .

  • Strong hands-on experience building data pipelines with Databricks, Apache Spark (PySpark), and Delta Lake .

  • Advanced SQL and Python , with strong data modeling skills across dimensional and Lakehouse patterns.

  • Experience with streaming ingestion using Structured Streaming, Auto Loader, Kafka, or Event Hubs .

  • Experience with workflow orchestration ( Databricks Workflows, Airflow, or Azure Data Factory ).

  • Experience with legacy platform migrations, ETL modernization, or managing data hygiene when porting old systems.

  • Strong problem-solving, collaboration, and communication skills.

  • Familiarity with Unity Catalog, data governance, access control, and PII handling .

  • Experience with dbt or an equivalent transformation framework .

  • Familiarity with secure coding standards and industry security best practices.

  • Experience delivering production data platforms at scale.

  • Upper-intermediate English level.

NICE TO HAVES

  • Experience with Infrastructure as Code (IaC) using Terraform and CI/CD using Azure DevOps.

  • Experience working with relational databases (specifically PostgreSQL) and data persistence concepts.

  • Familiarity with logging and monitoring tools (e.g., Dynatrace, CloudWatch, Databricks system tables).

  • Experience working in Agile or team-based development environments preferred.

PERKS AND BENEFITS

Professional growth : Accelerate your professional journey with mentorship, TechTalks, and personalized growth roadmaps.

Competitive compensation : We match your ever-growing skills, talent, and contributions with competitive USD-based compensation and budgets for education, fitness, and team activities.

A selection of exciting projects : Join projects with modern solutions development and top-tier clients that include Fortune 500 enterprises and leading product brands.

Flextime : Tailor your schedule for an optimal work-life balance, by having the options of working from home and going to the office – whatever makes you the happiest and most productive.

Skills

  • Databricks
  • PySpark
  • Delta Lake
  • SQL
  • Python
  • Data Warehousing
  • Unity Catalog

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