Join a forward-thinking engineering team focused on creating robust, scalable data platforms that enable intelligent decision-making. In this role, you'll design and implement data pipelines using Databricks, PySpark, and SQL, transforming raw data into analytics-ready formats that support business intelligence, advanced analytics, and AI applications.
What You’ll Do
- Build and maintain scalable ETL/ELT workflows using Spark and cloud-native technologies
- Design data lakehouse architectures and analytics platforms on cloud infrastructure
- Integrate data from diverse enterprise sources to create unified, high-quality datasets
- Optimize data models, pipeline efficiency, and Spark-based workloads
- Support migration from legacy ETL systems to modern cloud data platforms
- Collaborate with architects, analysts, and stakeholders in Agile project teams
- Contribute to engineering standards, reusable components, and team knowledge sharing
What We’re Looking For
- 2–5 years in data engineering or related technical roles
- Proven experience with Databricks, Apache Spark, and SQL
- Strong programming skills in Python and PySpark
- Familiarity with cloud data platforms such as Azure or AWS
- Solid understanding of data lakes, warehouses, and modeling principles
- Hands-on experience with Git and modern software development practices
- Ability to thrive in Agile and consulting environments
- Bachelor’s degree in Computer Science or equivalent practical experience
- Fluency in written and spoken English
Nice to Have
- Professional certifications in Databricks, Azure, or AWS
- Experience with AI agent development, including Databricks Agent Bricks or Mosaic AI
- Background in data platform modernization or ETL migration initiatives
- Familiarity with Delta Lake, Snowflake, or Microsoft Fabric
- Exposure to Power BI or similar analytics tools
- Experience working in global or multicultural settings
Technology Environment
Databricks, Apache Spark, PySpark, SQL, Azure, AWS, ETL/ELT, Git, Delta Lake, Snowflake, Microsoft Fabric, Power BI
