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Tier-1 brand, mid-level generalist role, metro location, and broad cloud/data skill requirements increase competition.
Core data engineering skills (SQL, Python, Spark, cloud) are highly transferable across industries.
Explicit years plus mandatory Snowflake/Databricks, Spark, cloud, SQL and Python requirements make shortlisting strict.
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Design, develop, and manage scalable data pipelines and structures supporting analytics, reporting, and downstream applications.
Ensure data quality, governance, and lineage across cloud platforms like Snowflake and Databricks, optimizing data ingestion and processing.
Collaborate cross-functionally to improve data sourcing and processing efficiency; mentor junior engineers and enhance internal data engineering tools and frameworks.
4–6+ years of experience in Data Engineering, preferably 5-7 years as indicated in relevant work experience.
Proficiency in advanced SQL and Python or similar programming languages.
Experience with cloud platforms such as AWS, GCP, or Azure and data platforms like Snowflake and Databricks.
Bachelor's degree preferred; combinations of coursework and experience or extensive related professional experience may be considered.
Strong individual contributor able to handle complex data engineering environments while mentoring junior engineers.
Experienced in building and optimizing data pipelines with focus on data quality, governance, and cloud data warehouse management.
Proficient in advanced SQL, Python, cloud ecosystem, and distributed computing frameworks (e.g., Apache Spark), with skill in CI/CD and workflow orchestration tools.