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Mid-level Pune data engineer with common Azure/Spark skills and reputable employer, high applicant density.
Role requires specific Azure and Spark expertise, moderately transferable across industries.
Multiple mandatory years and exact Azure/Spark/SQL stack requirements increase filtering rigor.
Design, develop, and maintain enterprise-level data pipelines for real-time and batch processing using Scala, Apache Spark, and Azure Databricks.
Collaborate with cross-functional teams to translate business requirements into scalable data solutions and operationalize machine learning models.
Ensure data quality, governance, and operational excellence, including mentoring junior engineers and participating in code reviews.
Minimum 3+ years overall experience in data engineering or related fields.
At least 2+ years experience building data pipelines for structured and unstructured data, including 1+ year with big data technologies like PySpark, Hadoop, Kafka, EventHub, Stream Analytics.
2+ years experience with Azure Data Factory, Azure Data Lake, Azure SQL DB, and Azure Synapse Analytics.
Bachelor's degree in Computer Science, Engineering, or equivalent practical experience is preferred but not strictly mandatory.
Experienced in translating complex business requirements into scalable data solutions working closely with stakeholders.
Skilled in big data and Azure platform technologies, with practical knowledge of data modeling, T-SQL, and performance tuning.
Comfortable working in Agile/Scrum environments with familiarity of DevOps, CI/CD pipelines, and source control systems like Git.