Data Engineer with DataBricks

About the Role:

We are looking for a skilled Data Engineer with strong expertise in Python, Scala, and Databricks to build and maintain scalable data processing solutions. The ideal candidate should have hands-on experience in developing batch and streaming data pipelines, optimizing big data workloads, and working in cloud-based data platforms.

Key Responsibilities:

• Design, develop, and maintain scalable data pipelines using Python, Scala, and Spark.
• Build and optimize ETL/ELT processes on the Databricks Lakehouse Platform.
• Develop high-performance data processing solutions for large-scale datasets.
• Work with structured, semi-structured, and unstructured data sources.
• Collaborate with Data Architects, Business Analysts, and Data Scientists to understand and implement data requirements.
• Perform performance tuning and optimization of Spark workloads.
• Design and maintain data models, data lakes, and data warehousing solutions.
• Implement data quality, governance, and security standards.
• Troubleshoot production issues and support data platform operations.
• Participate in Agile ceremonies, code reviews, and technical design discussions.

Required Skills:

Technical Skills:

• 5+ years of experience in Data Engineering.
• Strong programming skills in Python and Scala.
• Hands-on experience with Databricks and Apache Spark.
• Expertise in Spark SQL, DataFrames, Delta Lake, and Databricks Workflows.
• Strong SQL development and query optimization experience.
• Experience with ETL/ELT frameworks and data integration.
• Good understanding of Data Warehousing concepts and dimensional modeling.
• Experience working with cloud platforms such as:
  • Azure Databricks
  • AWS Databricks
  • GCP Databricks

If you are keen to join us, you will be part of an organization that values your contributions, recognizes your potential, and provides ample opportunities for growth. For more information, visit www.capco.com. Follow us on Twitter, Facebook, LinkedIn, and YouTube.