Data Engineer; Databricks

We’re looking for a data-driven professional to design, build, and optimize scalable data solutions using Databricks
. In this role, you’ll work closely with analytics, product, and business teams to turn raw data into reliable, high-quality datasets that power insights, reporting, and advanced analytics.

You’ll be hands-on with modern data platforms, cloud technologies, and distributed data processing, helping shape our data ecosystem end-to-end.

• Design, build, and maintain scalable data pipelines using Databricks and Apache Spark
• Develop and optimize ETL/ELT workflows for batch and streaming data
• Model, transform, and curate data for analytics, reporting, and downstream use cases
• Ensure data quality, reliability, and performance across datasets
• Collaborate with analytics, data science, and business stakeholders to understand data needs
• Optimize queries and Spark jobs for performance and cost efficiency
• Implement best practices for data governance, security, and access control
• Monitor pipelines and troubleshoot data issues in production environments

• Strong experience with Databricks (work spaces, notebooks, jobs, Delta Lake)
• Proficiency in SQL and Python (or Scala) for data processing
• Solid understanding of Apache Spark concepts and distributed computing
• Experience building data pipelines in a cloud environment (AWS, Azure, or GCP)
• Knowledge of data modeling concepts (star/snowflake schemas, dimensional modeling)
• Familiarity with version control (Git) and CI/CD practices for data workflows

• Experience with Unity Catalog, and Databricks performance tuning
• Experience supporting analytics or machine learning use cases
• Understanding of data governance, privacy, and compliance standards