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Metro hiring, mid-level generalist Data Engineer with broad Azure/Databricks skills increases applicant density.
Core Azure, Databricks, and PySpark skills transfer broadly, though P&G-specific frameworks reduce portability.
Explicit 3-5 years requirement plus mandatory Azure, Databricks, PySpark and DevOps skills.
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Design, develop, and maintain data infrastructure, data pipelines, and data models to support business objectives.
Ensure data quality, integrity, and optimization of distributed systems and data storage solutions.
Collaborate with cross-functional teams to identify data requirements and establish best practices for data engineering.
3-5 years of relevant experience.
Proficiency in Azure services including ADF, ADLS2, and Databricks.
Experience with Python, PySpark, and DevOps.
Familiarity with P&G frameworks like AI factory, Ultimate, and Pygentic.
Experienced in designing and managing large-scale data pipelines and infrastructure on Azure.
Comfortable working with distributed systems and data storage optimization.
Capable of collaborating across functions to align data solutions with business needs and standards.