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Tier-1 employer, popular Data Engineer title, mid-level experience, metro and broad technical requirements.
Core data engineering skills (ETL, Spark, Databricks, Snowflake) are highly transferable across industries.
Explicit years requirements and many mandatory technologies make shortlisting highly selective.
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Maintain, improve, and manipulate data in operational and analytics databases to ensure data integrity, quality, and security.
Design, deploy, and manage scalable data platforms across domains, focusing on Snowflake cloud data warehouse and Databricks for big data and streaming frameworks.
Enhance data efficiency and reliability through data transformation, enrichment, and governance within cloud environments, preferably Azure.
Bachelor's degree in Engineering (BE/BTECH) or equivalent experience.
At least 4 years of experience designing and supporting distributed, data-intensive systems.
Minimum 3 years working with relational databases (Oracle, SQL Server, MySQL) and 3+ years in Agile SDLC.
At least 2 years hands-on with ETL tools and delivering Data Platforms involving Snowflake; experience with big data tools like Kafka, Spark, Databricks; experience with cloud environments, preferably Azure.
Proven experience with programming languages such as Python, Java, Go, or Scala in large-scale data projects.
Experienced in big data and streaming frameworks combined with cloud-based data platform delivery, especially on Azure.
Familiarity with DevOps automation, CICD platforms, and monitoring tools indicating a capability for automated and scalable data platform operations.