Senior Data Engineer-Databricks, Snowflake, SQL, ETL,Spark,Data Warehouse
Optum (company site, opens in a new tab)3+ yrsGurugramOn-siteDirect career pageEst. 12–20 LPA
Posted on 23 Sept
Reach people at Optum
People at this company you can reach
Log in to see who works here
Create a free account or log in to see the people at Optum you could write to:
- Recruiters & HR
- People in this function
- Work addresses
Your match
Against your primary resume
Log in to see your match score
Create a free account or log in to unlock your CV match score across:
- Role fit
- Experience
- Industry relevance
Protocol Intelligence
How competitive this role is
Competition
Background fit
Strictness
Log in to see why each signal reads the way it does.
Job description
Structured overview of role & requirements
About This Role
- Design, develop, test, and optimize complex ETL pipelines to support data warehouse and BI environments utilizing Snowflake, Databricks, Spark, and SQL.
- Manage cloud infrastructure and job scheduling in Azure environment, including automation via GitOps tools like Jenkins and GitHub Actions, and deployment pipeline promotion from non-prod to production.
- Collaborate with cross-functional teams for developing AI-powered data solutions and maintain production support ensuring seamless data flow and system reliability.
Minimum Requirements
- Bachelor's or master's degree in Computer Science, IT, or equivalent (B.E/B.Tech/MCA/Graduation).
- 3+ years of experience in designing and developing ETL solutions within Data Warehousing and BI environments.
- Proficiency in Snowflake, Databricks, Spark, SQL, Hive, and job scheduling tools (Airflow).
- Experience working in cloud environments, preferably Azure, and familiarity with CI/CD pipelines using Jenkins and GitHub Actions.
Ideal Candidate Profile
- Experienced data engineer with strong expertise in ETL development and cloud-based data warehousing technologies, especially Snowflake and Databricks.
- Comfortable working in Agile/Scrum environments, capable of independently managing deployments, automation, and production support.
- Skilled at translating business data needs into scalable AI-powered and automated data solutions with proficiency in coordinating across technical and non-technical teams.