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Bengaluru metro role at a recognizable global employer with mid-level experience increases applicant density.
Platform-specific data engineering skills are transferable across industries but require cloud and tooling experience.
Explicit 4+ years plus mandatory 3+ years Databricks and Snowflake experience make filters stringent.
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Design, develop, and optimize large-scale data pipelines on Databricks and Snowflake platforms using PySpark, Delta Lake, and Snowflake SQL.
Manage Databricks notebooks, workflows, Snowflake ELT pipelines and performance tuning to ensure scalable and cost-efficient cloud data solutions.
Collaborate with data engineers, analysts, architects, and stakeholders to deliver enterprise data initiatives and support analytics and reporting.
Bachelor's degree in Computer Science, Information Technology, or related field (or equivalent experience).
4+ years of experience in data engineering or big data development.
3+ years of hands-on experience with Databricks, PySpark, and Azure Data Engineering services.
3+ years of hands-on experience with Snowflake, Snowflake SQL, ELT development, and related Snowflake features.
Experienced in building and optimizing production-scale PySpark applications and Snowflake ELT pipelines with strong performance tuning skills.
Comfortable with cloud data engineering environments including Azure Data Factory, Synapse, ADLS, and CI/CD pipelines in Git-based workflows.
Able to translate business data requirements into scalable technical solutions with emphasis on data governance, security, and cost optimization.