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Mid-level data engineer with metro location, generalist Azure/Databricks skills, and popular title increases competition.
Core data engineering skills are transferable across industries, though Azure/Databricks specialization adds some bias.
Explicit 3–7 years requirement and mandatory Azure, Databricks, SQL, Python skills.
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Develop, optimize, and maintain scalable Azure cloud data platforms and pipelines using Databricks and Azure data services.
Build and support ETL/ELT pipelines, SQL-based transformations, and data models focusing on performance and cost efficiency.
Collaborate with architects, analytics, QA, DevOps, and business stakeholders in a global delivery environment.
3 to 7 years of experience in data engineering with hands-on Azure & Databricks expertise.
Strong proficiency in SQL and Python, including PySpark for data engineering tasks.
Experience with Azure Data Lake Storage Gen2, Azure Data Factory, Azure Databricks, and Azure Synapse Analytics.
Bachelor’s or Master’s degree or equivalent; Microsoft Certified: Fabric Data Engineer Associate or Azure Solutions Architect Expert preferred.
Experienced individual contributor comfortable with building and troubleshooting end-to-end cloud data pipelines in Azure.
Familiarity with cloud-native data lakes, batch data processing, and basic streaming concepts.
Ability to work effectively across functions in a global delivery setup with strong technical collaboration skills.