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Tier-1 employer, mid-level generalist data role, metro location, and broad cloud/data stack increase competition.
Data engineering skills are transferable across industries but require specific cloud and data-platform experience.
Explicit 5–7 years requirement plus multiple mandatory cloud, Snowflake/Databricks, and Spark skills makes screening strict.
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Design, develop, and maintain scalable data pipelines and data structures for analytics, reporting, and downstream applications.
Ensure high-quality, reliable data delivery with efficient SQL transformations and ingestion frameworks across cloud platforms like Snowflake and Databricks.
Collaborate with cross-functional teams to improve data sourcing, processing efficiency, governance, and support junior engineers and internal tool improvement.
5-7+ years of experience in Data Engineering.
Strong advanced SQL query writing and optimization skills.
Proficiency in Python or similar programming languages.
Experience with cloud platforms (AWS/GCP/Azure), Snowflake/Databricks, and exposure to distributed computing frameworks like Apache Spark.
Experienced individual contributor comfortable in complex, scalable cloud data environments using advanced cloud data platforms such as Snowflake and Databricks.
Practitioner skilled in SQL optimization, Python programming, and building data ingestion and transformation pipelines with emphasis on data quality and governance.
Ability to mentor junior engineers and enhance internal data engineering tools and processes to increase operational efficiency.