We are Improving, an IT services firm focused on AI, Data, and Applications. We modernize legacy systems, build cloud-native platforms, and deliver future-ready solutions through collaborative, long-term partnerships that drive measurable outcomes. In this role, we are looking for Databricks Engineers to support the Tax and Audit group. You will help design, build, and operate data ingestion, transformation, and analytics pipelines that enable reliable reporting and downstream consumption. The work centers on turning raw data into structured, governed datasets—leveraging Apache Spark, Databricks, Delta Lake/Delta Tables, and columnar formats—so business stakeholders can trust the outputs used for audit and tax-related analytics.

Responsibilities

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, e

📌 Databricks Engineer (Argentina)
🏢 Improving South America
📍 Argentina