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Metro mid-senior role with general Python title plus desirable Databricks skills increases competition.
Requires specialized data engineering and Databricks expertise, limiting easy transfer across non-data roles.
Explicit 8–10 years requirement and mandatory Databricks/PySpark and data engineering skills.
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Architect, design, develop, and maintain scalable, high-performance data pipelines using Azure Databricks including Unity Catalog, SQL Warehouse, Workflows, and Delta Live Tables.
Define and implement data migration strategies and integrate Databricks solutions with various data sources and APIs to enable secure data access and downstream consumption.
Provide technical leadership and mentorship to junior engineers and collaborate with data scientists on data preparation for analytics and machine learning workloads.
8-10 years of professional experience in data engineering.
Strong skills in Python, PySpark, Scala, Java, SQL, and experience with RESTful APIs.
Bachelor’s or Master’s degree in Computer Science, Data Engineering, Data Science, or related technical discipline.
Comfortable with 3 days per week working from office (Pune, India).
Experienced in managing complex, established data landscapes and rapidly adapting to large volumes of new information.
Skilled in quality engineering, including building test frameworks and taking ownership of testing areas efficiently.
Capable of applying engineering solutions to automate and improve manual processes while supporting data science and machine learning workflows.