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Strong employer brand and metro location increase competition, balanced by senior, niche Databricks/AWS platform requirements.
Core Databricks/AWS platform skills transfer across industries, but mastering and market-data experience favor financial-domain candidates.
Explicit senior experience band plus mandatory Databricks, AWS, lakehouse, and mastering expertise enforce strict shortlisting.
Lead transition and implementation of data pipelines into AWS cloud-native and Databricks lakehouse platforms, ensuring platform consistency, reliability, and observability.
Define and operationalize scalable, reusable onboarding patterns supporting diverse data domains, including integration with enterprise data mastering and governance platforms.
Provide senior technical leadership on data platform engineering, influencing architecture and engineering standards without direct people management.
8+ years experience in data engineering, cloud data architecture, or related domains.
Strong hands-on expertise with AWS data services (S3, Glue, Lambda, Kinesis, Lake Formation) and Databricks lakehouse technologies including pipeline migration and governance.
Experience with modern data engineering best practices including version control, automated testing, CI/CD, release automation, and monitoring.
Location: Hyderabad; Shift: 12 to 9 pm IST; Office work model: 2 days/week or 9 days per month on-site.
Senior technical individual contributor experienced navigating complex, distributed, globally collaborative environments with cross-time zone delivery experience.
Practitioner with deep expertise integrating data mastering/MDM platforms and data governance in production pipeline workflows.
Experienced in applying AI/LLM-assisted software engineering tools in data engineering contexts to improve pipeline quality, testing, and operational support.