Should have 10+ Years of Relevant Experience
3+ Years of Experience in developing Big Data applications using Spark, Hive, Sqoop, Kafka, and Map Reduce
3+ years of experience in Agile/Kanban
6+ years of experience in ETL
6+ years of experience in DWH
4+ years of Experience with object-oriented/object function scripting languages: Python, Scala etc
Experience in designing and building dimensional data models to improve accessibility,
efficiency, and quality of data
Should be proficient in writing Advanced SQLs, Expertise in performance tuning of SQLs.
Experience with data science and machine learning tools and technologies is a plus
6+ years of Experience with relational SQL and NoSQL databases, including Postgres and Cassandra.
5+ Years of Experience with Azure cloud nativce services Azure DataFactory, Azure
DataBricks, ADLS.
Azure DataLake 5+ years of experiences
Azure SQL/Snowflake or similar 5+ years of experiences
Talend 3+ years of experiences
Jira/Azure DevOps or similar 3+ years of experiences
Confluence or similar 3+ years of experiences Should be able to maintains scalable data pipelines and builds out new API integrations to support continuing increases in data volume and complexity
Ability to perform data analysis required to troubleshoot data related issues and assist in the resolution of data issues.
Implements processes and systems to monitor data quality, ensuring production data is always accurate and available for key stakeholders and business processes that depend on it.
Strong skills in DevOps practices and automation are important for streamlining data
engineering operations.
Should have experience with CI/CD (Continuous Integration/Continuous Deployment)
pipelines, version control systems (e.g., Git), and automated testing frameworks