About this role
About the Role The data wranglers of the business world transform raw data into a usable format for analysis, building the infrastructure that empowers data scientists and analysts to unlock valuable insights. They identify trends and develop strategies, bridging data and actionable decisions to drive organizational efficiency and performance. What You'll Do
- Design and implement ETL/ELT pipelines using Spark SQL and Python within Databric
- Build and maintain data infrastructure that enables analysis by data scientists and analysts
- Optimize data pipelines and engineering workflows for performance and cost efficiency What We're Looking For
- At least 5+ years’ experience with SparkSQL, Python and PySpark for data engineering workflow
- Strong proficiency in dimensional modeling and star schema design for analytical workloads
- Experience implementing automated testing and CI/CD pipelines for data workflows
- Familiarity with GitHub operations and collaborative development practices
- Demonstrated ability to optimize engineering workflow jobs for performance and cost efficiency
- Experience with cloud data services and infrastructure (AWS, Azure, or GCP)
- Proficiency with IDE tools such as Visual Studio Code for efficient development Nice to Have
- Databricks platform experience will be a plus