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Well-known employer, metro Bangalore, hybrid role, and common mid-level Data Engineer title drive high competition.
Data engineering skills (ETL, pipelines, cloud) are broadly transferable across industries.
Moderate filters: specific data technologies and certifications listed but no explicit years requirement.
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Develop, implement, and optimize data ingestion, storage, and retrieval solutions including ETL pipelines for data lake/warehouse environments.
Collaborate with data scientists and analysts to deliver relevant datasets meeting data requirements and maintain data quality and pipeline integrity.
Troubleshoot data-related issues and research new data technologies and tools for continuous improvement.
Bachelor's or Master's degree in Business Analytics, Computer Science, Statistics, or Data Science.
Work Experience Required: Not explicitly mentioned in the JD.
Proficiency in data engineering related technologies with certifications such as Databricks Certified Associate Developer for Apache Spark, Microsoft Certified: Azure Data Engineer Associate, or Oracle Database 12c Certified Implementation Specialist.
Ability to work in hybrid remote setup and flex time shift based in India.
Experience working in Agile methodology and collaborating with cross-functional teams like data scientists and analysts to deliver data solutions.
Strong technical skills in cloud computing, data engineering, and platforms like Snowflake and Apache Spark as evidenced by relevant certifications.
Comfortable operating in fast-moving, innovation-driven, hybrid work environments focusing on AI-powered digital transformation projects.