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Sr Data Platform Engineer

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Amgen

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Location:
India , Hyderabad

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Category:
IT - Software Development

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Contract Type:
Not provided

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Salary:

Not provided
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Job Responsibility:

  • Act as a platform lead for delivery of data platform capabilities that enable next-gen data platform architecture, with a strong focus on Databricks platform and DQ platform features and services
  • Evaluate and enable Databricks platform capabilities through technical assessments and proof‑of‑concepts (PoCs), ensuring alignment with next-gen data platform architectural patterns and enterprise standards
  • Design, build, and productionize reusable platform frameworks, accelerators, and reference implementations that can be leveraged by next-gen data platform delivery teams (excluding ownership of data pipeline architecture or implementation)
  • Enable data governance, metadata layer, and data bundle capabilities by designing and implementing platform‑level integrations between Databricks and Collibra, Amgen’s enterprise data governance platform
  • Build platform‑level tooling and automation to support proactive governance, cost optimization, and best‑practice enforcement across Databricks and related data platform services
  • Define and enable platform observability capabilities, including KPIs, metrics, and telemetry for monitoring performance, usage, reliability, and cost of Databricks services
  • Identify and implement governed self‑service platform capabilities for data engineers through self-service portal, using Python‑based microservices deployed on Docker and Kubernetes
  • Lead user enablement and adoption initiatives, including onboarding content, guided learning experiences, workshops, and best‑practice sharing for the Databricks user community
  • Drive engineering excellence and adoption of AI across platform capabilities and solutions built, promoting modern engineering practices, automation, and responsible use of AI‑driven features
  • Enable key business programs and strategic initiatives by translating initiative‑driven requirements into scalable, reusable data platform capabilities, in alignment with next-gen data platform principles
  • Collaborate closely with Enterprise Data Architecture (EDA), governance, platform operations, and delivery teams to ensure platform capabilities are aligned, consumable, and enterprise‑ready

Requirements:

  • Master’s degree OR Bachelor’s degree in computer science or engineering field and 8 to 13 years of relevant experience
  • Strong hands‑on experience with various capabilities of Databricks, from Compute to Storage and from Unity Catalog to Data Engineering to BI and AI/ML capabilities, with a focus on governance and enterprise enablement
  • Proven hands‑on experience with cloud platforms, with strong preference for AWS (experience with Azure or GCP also acceptable)
  • Experience leading Data Quality platform initiatives (e.g., Ataccama, Monte Carlo), including tool evaluation, implementation, enterprise-wide adoption, and integration with enterprise DQ solutions
  • Experience owning and managing Databricks platform environments, including workspace architecture, environment strategy (dev/test/prod), and lifecycle management at scale
  • Proven ability to establish and enforce platform standards and operating models, including cluster policies, cost management, and workload orchestration frameworks
  • Strong focus on platform enablement and developer experience, including building reusable frameworks, defining best practices, and supporting engineering teams in adopting the platform effectively
  • Exposure to AI/ML capabilities on Databricks, including enabling AI‑driven features or accelerating adoption of AI‑assisted engineering practices
  • Solid knowledge of SQL and relational / dimensional data modelling, sufficient to support platform integrations, governance, and observability use cases
  • Experience working with core AWS services such as EKS, EC2, S3, Lambda, Glue, EMR, RDS, and Redshift/Spectrum, particularly in platform or shared‑services contexts
  • Strong analytical and problem‑solving skills, with the ability to design scalable, reusable solutions for complex data platform challenges
  • Experience working in Agile delivery environments, with exposure to tools such as Jira or Jira Align

Nice to have:

  • Experience contributing to or enabling self‑service platforms or portals (front‑end or API‑driven), including collaboration with front‑end teams (e.g., React‑based portals)
  • Proficiency in Python‑based microservices development, including designing and deploying APIs and services that enable platform capabilities
  • Experience building platform APIs and services with Databricks SDKs and REST APIs for provisioning, managing, or governing Databricks environments and managing workspaces, clusters, jobs, users, permissions, and related platform features
  • Experience with DQplatforms like Ataccama or Monte Carlo used in association with Data Engineering platforms
  • Familiarity with platform observability, telemetry, or cost‑optimization patterns for large‑scale data platforms
  • Experience enabling data governance, metadata, or lineage integrations between data platforms and enterprise governance tools (e.g., Collibra)
  • Experience working with SQL/NoSQL databases and vector databases, particularly in the context of LLM‑enabled or AI‑assisted platform solutions
  • Experience with CI/CD pipelines, containerization (Docker), and Kubernetes/EKS, and applying these practices to enterprise platform services
  • Strong understanding of software engineering best practices, including version control, automated testing, continuous integration, and production‑grade design
  • Certifications (preferred but not required): AWS Certified Data Engineer, Databricks Certification, SAFe Agile Certification

Additional Information:

Job Posted:
May 04, 2026

Employment Type:
Fulltime
Work Type:
On-site work
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