Data Engineer - Databricks

Desired Competencies (Technical/Behavioral Competency)

• Strong experience in programming languages such as Python, PySpark, or Scala for data engineering tasks.
• Design, develop, and maintain scalable and robust data pipelines on Databricks
• Hands-on experience with cloud technologies, expertise in AWS/Azure data engineering services to handle large-scale data processing and real-time data streams.
• In-depth knowledge of data warehousing solutions such as Amazon Redshift, Google BigQuery, and Snowflake for building and managing data warehouses.

Proficiency in designing, developing, and maintaining ETL (Extract, Transform, Load) processes using cloud services, ADF, Glue etc

Responsibility of / Expectations from the Role

• Design, develop, and maintain scalable data pipelines for extracting, transforming, and loading data from various sources to ensure seamless data flow and accessibility.
• Collaborate with cross-functional teams to integrate data from multiple disparate sources, ensuring consistency, accuracy, and reliability of data.
• Optimize data processing workflows and storage solutions for performance, scalability, and cost-efficiency
• Implement data quality checks and validation processes to ensure the accuracy, completeness, and consistency of data throughout the data lifecycle.
• Monitor the performance of data pipelines and infrastructure, identifying and resolving issues to maintain system stability and reliability.