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Popular mid-level Data Engineer role, strong employer brand, metro location and broad skillset increases competition.
Core data engineering skills are transferable across industries despite optional automotive domain exposure.
Mandatory PySpark, Databricks, AWS and explicit 3-5 years experience makes screening stringent.
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Design, implement, and manage scalable data pipelines and data platforms in cloud environments to support user data access and aggregation.
Integrate data from multiple sources ensuring quality, consistency, and optimize data systems for reliability and efficiency.
Collaborate with data scientists and analysts to support infrastructure needs, monitor and troubleshoot data pipelines, and maintain documentation.
Bachelor's degree in Computer Science/IT or Master's in Computer Application with minimum 60% marks.
3-5 years of work experience in Data Engineering, Big Data, Cloud Computing, or Analytics projects.
Proficiency in PySpark (mandatory), SQL, Python and experience with data platforms like Databricks.
Experience with AWS S3 storage, Medallion Architecture layers, Delta/Iceberg formats, and data schema designs such as Star and Snowflake.
Experience working in fast-paced Agile-Scrum environments, capable of working independently and in teams.
Technical expertise in next-generation ETL/ELT tools and data consolidation frameworks within data ecosystems.
Familiarity with IoT time series data or automotive data domain is a plus but not mandatory.