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Remote role, metro locations, and a visible data engineer/architect title increase applicant density and competition.
Specialized lakehouse, Databricks and governance skills transfer across industries, so moderate background sensitivity.
Multiple mandatory platform, tooling and architecture requirements create moderate filtering despite no explicit years requirement.
Define and build the target-state data lakehouse architecture, enterprise data warehouse, data marts, and data models to enable trusted, scalable, and governed data infrastructure.
Develop, operate, and maintain ingestion and ETL/ELT pipelines from multiple sources ensuring reliable, incremental, and observable data delivery.
Implement platform security, governance, metadata management, and build reusable data products to support reporting, traceability, compliance, impact measurement, and AI/ML use cases.
Degree in Computer Science, Engineering or related field, or equivalent practical experience.
Proven hands-on experience in data engineering and architecture, including lakehouse, data warehouse design, ETL/ELT pipeline development, and migration/reconciliation of large datasets in production.
Experience with Microsoft Fabric, Azure Synapse, Azure Data Lake Storage, Power BI, Databricks, Spark/PySpark, Delta Lake, Unity Catalog, and orchestration tools like Databricks Workflows or Apache Airflow.
Fluency in written and spoken English; role based in Delhi or Ahmedabad (hybrid); work experience required: Not explicitly mentioned in the JD.
Experienced in building and operating large-scale production data platforms combining architecture and hands-on delivery, including medallion (bronze/silver/gold) lakehouse patterns and distributed processing at scale.
Strong familiarity with Microsoft data ecosystem and cloud-native data engineering tools, with knowledge of data governance, security, and cost optimization on consumption-based platforms.
Ability to translate complex legacy system data into reliable, governed data products supporting diverse analytics and AI/ML needs in a mission-driven, multicultural environment.