Position Summary: Data engineer on the Data integration team Job Description & Responsibilities: Work with business and technical leadership to understand requirements. Design to the requirements and document the designs Ability to write product-grade performant code for data extraction, transformations and loading using Spark, Py-Spark Do data modeling as needed for the requirements. Write performant queries using Teradata SQL, Hive SQL and Spark SQL against Teradata and Hive Implementing dev-ops pipelines to deploy code artifacts on to the designated platform/servers like AWS. Troubleshooting the issues, providing effective solutions and jobs monitoring in the production environment Participate in sprint planning sessions, refinement/story-grooming sessions, daily scrums, demos and retrospectives. Experience Required: Overall 8-10 years of experience Experience Desired: Strong development experience in Spark, Py-Spark, Shell scripting, Teradata. Strong experience in writing complex and effective SQLs (using Teradata SQL, Hive SQL and Spark SQL) and Stored Procedures Health care domain knowledge is a plus Primary Skills: Excellent work experience on Databricks as Data Lake implementations Experience in Agile and working knowledge on DevOps tools (Git, Jenkins, Artifactory) AWS (S3, EC2, SNS, SQS, Lambda, ECS, Glue, IAM, and CloudWatch) Databricks (Delta lake, Notebooks, Pipelines, cluster management, Azure/AWS integration Additional Skills: Experience in Jira and Confluence Exercises considerable creativity, foresight, and judgment in conceiving, planning, and delivering initiatives.
