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Tier-1 employer, metro location and mid-level data role with specialized Databricks/Snowflake skills.
Databricks and Snowflake data engineering skills are transferable across industries but need specific cloud/tool expertise.
Mandatory 4+ years plus specific Databricks, Snowflake, PySpark and Azure skills enforce strict filters.
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Design, develop, and optimize scalable data pipelines and transformations using Databricks (PySpark, Delta Lake) and Snowflake (SQL, ELT workflows).
Manage and tune Databricks notebooks, workflows, Snowflake warehouses, pipelines, and performance to ensure efficiency and cost governance.
Collaborate with data engineers, architects, analysts, and business stakeholders to support enterprise data initiatives and maintain compliance and documentation.
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 hands-on experience with Databricks, PySpark, Delta Lake, and Azure Data Engineering services.
3+ years hands-on experience with Snowflake SQL, Snowflake ELT development, performance tuning, and pipeline orchestration.
Experienced in building and maintaining complex, cloud-scale data pipelines integrating Databricks, Snowflake, and Azure Data Factory.
Strong capability in performance tuning and cost optimization of cloud data platforms and pipelines.
Comfortable working with cross-functional teams to convert business data requirements into robust technical solutions.