{"id":38397,"url":"https://alion.io/job/amgen-senior-data-engineer","title":"Senior Data Engineer","company":{"id":4775,"name":"Amgen","domain":"amgen.com","url":"https://alion.io/company/amgen","size_band":"5000+","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Workday","truth_index":{"grade":"A","score":85,"open_postings":349,"ghost_share":0,"stale_share":0.579,"repost_share":0.003,"time_to_fill_p50_days":42,"computed_at":"2026-10-27T05:46:45Z"}},"role":"Data Science","role_family":"Data Science","seniority":"senior","employment_type":"full_time","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Hyderabad, India"],"countries":["IN"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":24000,"max_usd":52000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":75},"experience_years_min":9,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Agile","optional":false},{"name":"AWS","optional":false},{"name":"CI/CD","optional":false},{"name":"Databricks","optional":false},{"name":"Delta Lake","optional":false},{"name":"ETL/ELT","optional":false},{"name":"Git","optional":false},{"name":"Least Privilege","optional":false},{"name":"pySpark","optional":false},{"name":"Python","optional":false},{"name":"Spark","optional":false},{"name":"SQL","optional":false},{"name":"Amazon Kinesis","optional":true},{"name":"Apache Kafka","optional":true},{"name":"Copilot","optional":true},{"name":"Embeddings","optional":true},{"name":"OpenAI Codex","optional":true},{"name":"RAG","optional":true}],"status":"live","first_seen_at":"2026-08-04T00:00:00Z","employer_posted_date":"2026-09-28","last_verified_at":"2026-10-27T10:55:12Z","board_verified":true,"closed_at":null,"days_open":84,"trust":{"level":"ok","repost_count":1,"flags":[],"days_open":84},"description":"Career Category\nEngineeringJob Description\nRole Description\nWe are seeking an experienced Senior Data Engineer to lead the design, development, and delivery of scalable enterprise data solutions. This role will build and optimize batch and real-time data pipelines, reusable integration frameworks, and governed data platforms that support analytics, AI, and self-service data access.\nThe ideal candidate has deep expertise in Databricks, Apache Spark, AWS, data modeling, governance, and production operations. The role also provides technical leadership, defines engineering standards, mentorsother engineers, and partners with architecture, business, analytics, data science, and DevOps teams.\nExperience in manufacturing, biotechnology, pharmaceutical, life sciences, or another regulated industry is preferred.\nRoles and Responsibilities\nLead the design and development of scalable batch and real-time ETL/ELT pipelines.\n\nOwn complex data solutions from requirements and design through deployment and production support.\n\nBuild cloud-based lakehouseand data-platform solutions using Databricks and AWS.\n\nDevelop reusable, metadata-driven data integration frameworks.\n\nIntegrate structured, semi-structured, and unstructured data from enterprise, manufacturing, API, and third-party sources.\n\nOptimize Spark workloads, Databricks compute, SQL queries, partitioning, storage, and caching for performance and cost.\n\nImplement workflow orchestration, monitoring, alerting, data-quality controls, and recovery processes.\n\nDevelop CI/CD pipelines and automated testing for data solutions.\n\nImplement metadata management, lineage, cataloging, governance, RBAC, and data-security controls.\n\nDefine data models, data contracts, integration patterns, and reusable engineering standards.\n\nLead architecture reviews, code reviews, troubleshooting, and root-cause analysis.\n\nMentor engineers and provide technical guidance across delivery teams.\n\nCollaborate with architects, analysts, data scientists, product teams, and DevOps teams.\n\nSupport estimation, sprint planning, technical roadmaps, and delivery-risk management.\n\nEvaluate emerging technologies and recommend solutions based on scalability, security, maintainability, and business value.\n\nParticipate in operational support, including occasional off-hours support.\n\nBasic Qualifications\nOne of the following:\nMaster’s degree in Computer Science, Engineering, Information Technology, Data Science, or a related field and at least 7 years of relevant experience.\n\nOR\nBachelor’s degree in a related field and at least 9 years of relevant experience.\n\nMust-Have Skills\nAdvanced hands-on experience with Databricks, Apache Spark, PySpark, Spark SQL, Delta Lake, Python, and SQL.\n\nExperience designing and operating production-grade batch and streaming pipelines.\n\nStrong understanding of distributed computing, lakehousearchitecture, data warehousing, and data integration.\n\nExperience with Databricks Workflows or comparable orchestration tools.\n\nStrong experience with AWS data, compute, storage, security, and monitoring services.\n\nExperience with Spark performance tuning, cluster optimization, partitioning, and cost management.\n\nExperience with Git, CI/CD, automated testing, monitoring, and production deployment.\n\nExperience implementing data quality, metadata management, lineage, governance, and access controls.\n\nStrong understanding of RBAC, least privilege, encryption, auditability, and regulated-data requirements.\n\nExperience leading technical design, code reviews, and complex production implementations.\n\nAbility to define reusable patterns, engineering standards, and development best practices.\n\nStrong communication, collaboration, mentoring, and problem-solving skills.\n\nExperience working in Agile or Scaled Agile delivery environments.\n\nPreferred Qualifications\nExperience in biotechnology, pharmaceutical, life sciences, manufacturing, or another regulated industry.\n\nExperience with Unity Catalog, data products, Data Fabric, Data Mesh, or similar enterprise data architectures.\n\nExperience building APIs and secure data services.\n\nExperience with relational, NoSQL, analytical, operational, or vector databases.\n\nExperience with OLAP and OLTP data modeling and performance tuning.\n\nExperience with Kafka, Kinesis, or other streaming technologies.\n\nExperience supporting AI and Generative AI solutions, including RAG, embeddings, vector search, and governed enterprise data access.\n\nFamiliarity with AI-assisted development tools such as GitHub Copilot, OpenAI Codex, or equivalent platforms.\n\nPreferred Certifications\nAWS Certified Data Engineer or another relevant AWScertification.\n\nDatabricks Certified Data Engineer Associate or Professional.\n\nScaled Agile Framework certification.\n\nSoft Skills\nExcellent analytical and troubleshooting skills.\n\nStrong written, verbal, presentation, and stakeholder-communication skills.\n\nHigh degree of ownership, initiative, and self-motivation.\n\nAbility to manage multiple priorities in a fast-paced environment.\n\nAbility to work effectively with global and virtual teams.\n\nStrong attention to detail and commitment to engineering quality.\n\nAbility to influence technical decisions and drive work to completion.\n\n.","description_format":"text","description_chars":5229,"description_truncated":false,"requirements":{"experience_years_min":9,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":{"level":"bachelor","optional":false},"security_clearance":false,"languages":[]},"benefits":[],"hiring_locations":[],"hiring_excludes":[],"relocation_offered":false,"industries":["Biotechnology","Health Care","Immunology & Inflammation Therapeutics","Cardiometabolic Therapeutics"],"lifecycle":[{"event":"open","at":"2026-08-04T00:00:00Z"},{"event":"close","at":"2026-08-05T15:36:17Z"},{"event":"reopen","at":"2026-09-29T01:01:49Z"}],"visa":[],"liveness":{"score":12,"band":"cold","label":"Long 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