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Amgen

Makes biotech medicines for serious illnesses

Data Platform Lead

Platform EngineeringConfirmed live in the last 24 hours
Full-timeHyderabad, Telangana, IndiaNo salary listedIn-person

About the Job

Requirements

  • A Master's degree, or a Bachelor's degree in computer science or an engineering field, and 8 to 13 years of relevant experience.
  • Strong hands-on experience with Databricks capabilities across compute, storage, Unity Catalog, data engineering, business intelligence, and AI/ML, particularly governance and enterprise enablement.
  • Hands-on experience with cloud platforms; AWS is preferred, and Azure or Google Cloud Platform experience is acceptable.
  • Experience leading data quality platform initiatives, including tool evaluation, implementation, enterprise-wide adoption, and integration with enterprise data quality solutions.
  • Experience owning and managing Databricks platform environments, including workspace architecture, development/test/production environment strategy, and lifecycle management at scale.
  • Ability to establish and enforce platform standards and operating models, including cluster policies, cost management, and workload orchestration frameworks.
  • Experience in platform enablement and developer experience, including building reusable frameworks, defining best practices, and helping engineering teams adopt the platform.
  • Exposure to Databricks AI/ML capabilities, including enabling AI-driven features or accelerating adoption of AI-assisted engineering practices.
  • Knowledge of SQL and relational and dimensional data modeling sufficient to support platform integrations, governance, and observability use cases.
  • Experience with core AWS services including EKS, EC2, S3, Lambda, Glue, EMR, RDS, and Redshift/Spectrum, particularly in platform or shared-services contexts.
  • 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.
  • Strong communication skills to explain platform concepts, trade-offs, and best practices to senior technical and business stakeholders.
  • Ability to troubleshoot complex technical, governance, and integration challenges.
  • Ability to translate technical platform concepts into clear, business-relevant language for diverse audiences.
  • Experience working effectively across architecture, governance, platform, and delivery teams.
  • Proactive ownership in driving engineering excellence, platform maturity, and adoption outcomes.
  • Ability to manage multiple priorities while maintaining quality, reliability, and reusability.
  • Planning and execution skills, including estimating, planning, and delivering platform capabilities across multiple initiatives.

Responsibilities

  • Lead delivery of data platform capabilities that enable next-generation data platform architecture, focusing on Databricks and data quality platform features and services.
  • Evaluate and enable Databricks platform capabilities through technical assessments and proofs of concept, aligning them with next-generation architecture patterns and enterprise standards.
  • Design, build, and productionize reusable platform frameworks, accelerators, and reference implementations for next-generation 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.
  • Build platform-level tooling and automation for 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 Databricks service performance, usage, reliability, and cost.
  • Identify and implement governed self-service platform capabilities for data engineers through a 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 AI adoption across platform capabilities and solutions, promoting modern engineering practices, automation, and responsible use of AI-driven features.
  • Translate initiative-driven requirements into scalable, reusable data platform capabilities aligned with next-generation data platform principles.
  • Collaborate with Enterprise Data Architecture, governance, platform operations, and delivery teams to ensure platform capabilities are aligned, consumable, and enterprise-ready.

Desired Qualifications

  • Experience contributing to or enabling self-service platforms or portals, including front-end or API-driven platforms and collaboration with front-end teams such as React-based portal teams.
  • 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 to provision, manage, or govern Databricks environments, workspaces, clusters, jobs, users, permissions, and related platform features.
  • Experience with data quality platforms such as Ataccama or Monte Carlo 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 such as Collibra.
  • Experience with SQL/NoSQL databases and vector databases, particularly for LLM-enabled or AI-assisted platform solutions.
  • Experience with CI/CD pipelines, containerization with Docker, and Kubernetes/EKS, and applying these practices to enterprise platform services.
  • Understanding of software engineering best practices, including version control, automated testing, continuous integration, and production-grade design.
  • AWS Certified Data Engineer, Databricks, or SAFe Agile certifications are preferred but not required.

About the Company

Amgen

Makes biotech medicines for serious illnesses

Amgen develops and makes biologic medicines, which are drugs built from proteins and antibodies grown in living cells, for serious conditions such as heart disease, cancer, and bone loss. Its anemia drug Epogen, approved in 1989, became one of the biotechnology industry's first blockbuster medicines. Amgen grows these drugs in large tanks called bioreactors, and its products include the cholesterol drug Repatha, the bone-building drug Evenity, and the severe asthma drug Tezspire. It earns money by selling these medicines, mostly through large drug wholesalers that supply hospitals and pharmacies. Amgen was founded in 1980 and is based in Thousand Oaks, California.

Company size
10,001+
Company stage
IPO
Headquarters
Thousand Oaks, CA
Founded
1980

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