Databricks Engineer (Tax & Audit)

We need someone with proven, hands-on software development experience and strong data engineering depth for Databricks-based delivery.

• 5+ years of hands-on software development experience.

• Strong expertise in Apache Spark , with a proven record of delivering on Databricks .

• Proficient in Python with advanced data engineering skills using PySpark , Pandas , and related libraries.

• Experience developing and maintaining unit tests for Databricks workloads.

• Solid understanding of columnar storage (e.g., Parquet ).

• Hands-on experience with Delta Lake / Delta Tables .

• Ability to handle small to large data volumes , including performance tuning and optimizations.

• Demonstrated ability to build data ingestion , transformation , and analytics pipelines .

• Strong analytical and problem-solving skills with close attention to detail .

• Comfort working with Databricks workflows and delivering outcomes reliably.

How we work (traits we value):

• Quality mindset: careful validation, correctness, and attention to details—especially important for Tax and Audit contexts.

• Ownership: you take responsibility for pipeline stability, performance, and maintainability.

• Communication: we expect clear collaboration with technical and non-technical stakeholders to align data outputs with business needs.

• Continuous improvement: you actively look for ways to simplify pipelines, improve performance, and strengthen testing coverage.

Responsabilidades: We are looking for Databricks Engineers to join our Tax and Audit group and strengthen the team’s delivery across the data lifecycle.

• Build and maintain Apache Spark solutions delivered on Databricks , including scalable transformations and production-ready workloads.

• Develop and optimize data ingestion , transformation , and analytics pipelines that handle small to large data volumes.

• Use advanced Python and PySpark to implement efficient data engineering patterns (e.g., batch processing, enrichment, and data quality steps).

• Apply strong understanding of columnar storage (e.g., Parquet ) and deliver production data sets using Delta Lake / Delta Tables .

• Write and maintain unit tests for Databricks workloads to improve reliability and reduce regressions.

• Perform performance tuning and optimization (Spark execution efficiency, partitioning strategies, and query/read/write improvements).

• Collaborate with stakeholders to clarify requirements, translate analytics needs into technical designs, and ensure outputs meet accuracy and timeliness expectations.

• Own Databricks workflows end-to-end—from development through deployment and ongoing support.

• Optionally contribute to Databricks DevOps practices (nice to have), improving CI/CD, environment management, and release processes.

Goals: deliver dependable data products for Tax and Audit workflows, improve pipeline performance and maintainability, and ensure high-quality results through testing and careful attention to detail.

Deseable: • Familiarity with Databricks DevOps practices (e.g., CI/CD concepts, environment/version management, and deployment workflows).

• Experience contributing to data governance patterns such as dataset documentation, consistency checks, and maintainable conventions across teams.

• Prior exposure to testing strategies beyond unit tests (e.g., integration tests for pipelines) to further improve reliability.

Beneficios: • Comprehensive medical, dental, vision, and life insurance

• Mental health support

• Savings Fund & Corporate Retirement Plan

• Paid time off, vacation bonus, and Christmas bonus

• Career development, certifications, and continuous learning

• TotalPass wellness program

• Collaborative culture with internal events and technical communities

• Opportunity to work on innovative global projects with cutting-edge technologies