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Popular mid-level Data Engineer role in Gurgaon with common Azure/Databricks skills and 6–10 years experience.
Core data engineering skills are transferable across industries, though insurance domain experience is a preferred advantage.
Specific 6–10 years plus mandatory Azure, Databricks, PySpark, Delta Lake and governance requirements increase filtering.
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Lead design, development, and optimization of scalable, high-performance data pipelines ensuring reliable ingestion and transformation across distributed systems.
Define and enforce enterprise-grade data quality frameworks with validation rules, anomaly detection, and reconciliation processes to maintain data accuracy and integrity.
Own end-to-end monitoring and reliability of data platforms with observability practices, root-cause analysis, and governance adherence to ensure seamless continuity and compliance.
6–10 years of hands-on data engineering experience with strong expertise in Azure cloud and Databricks platforms.
Bachelor’s degree in Computer Science, Information Technology, Engineering, or related discipline.
Proficient in PySpark, Python, SQL; experience with Azure Data Factory, Azure Databricks, Azure Data Lake Storage, Delta Lake, and enterprise data warehousing.
Experience with Databricks features including Delta Live Tables, Auto Loader, Unity Catalog, and workflow orchestration; knowledge of data governance, quality, and secure data handling.
Experienced in architecting and optimizing large-scale, distributed data pipelines in cloud environments, particularly Azure and Databricks.
Familiar with implementing data governance and compliance frameworks, preferably in insurance domain use cases and regulatory settings.
Capable of leading technical initiatives, mentoring teams, and collaborating effectively with cross-functional stakeholders in Agile environments.