Data Engineer 2

Education & Experience:

Technical Skills:

• Strong expertise in managing big data technologies (Python, SQL, PySpark, Spark) with a proven track record of working on large-scale data projects
• Strong Databricks experience
• Strong database/backend testing with the ability to write complex SQL queries for data validation and integrity
• Strong streaming and real-time API/service validation including automation
• Experience with automated web services (WSDL) and microservices (REST) using custom scripts and assertions for data validation and data-driven testing
• Experience with cloud platforms such as Amazon Web Services (AWS), Microsoft Azure, or Google Cloud Platform (GCP)
• Proficiency in object-oriented programming and software design patterns
• Experience working in DevOps model, including installing, configuring, and integrating automation scripts on continuous integration tools (CI/CD) and GitHub for real-time test suite execution and troubleshooting
• Experience with Unit, Functional, Integration, User Acceptance, System, and Security testing of data pipelines
• Strong experience in designing and implementing data pipelines, ETL processes, and workflow automation
• Familiarity with data warehousing concepts, dimensional modeling, data governance best practices, and cloud-based data warehousing platforms (e.g., AWS Redshift, Google BigQuery, Snowflake)
• Familiarity with cutting-edge AI technologies and demonstrated ability to rapidly learn and adapt to emerging concepts and frameworks

Core Competencies:

Scheduled Weekly Hours

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