{"id":4077664,"url":"https://alion.io/job/amgen-principal-data-engineer-python-backend","title":"Principal Data Engineer – Python Backend","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":"B","score":83,"open_postings":337,"ghost_share":0,"stale_share":0.68,"repost_share":0.018,"time_to_fill_p50_days":42,"computed_at":"2026-11-11T05:49:22Z"}},"role":"Backend","role_family":"Backend","seniority":"lead","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":null,"experience_years_min":12,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AI Agents","optional":false},{"name":"CI/CD","optional":false},{"name":"Databricks","optional":false},{"name":"Django","optional":false},{"name":"ETL/ELT","optional":false},{"name":"FastAPI","optional":false},{"name":"Flask","optional":false},{"name":"Git","optional":false},{"name":"pySpark","optional":false},{"name":"Python","optional":false},{"name":"Rest API","optional":false},{"name":"Spark","optional":false},{"name":"SQL","optional":false},{"name":"Airflow","optional":true},{"name":"Apache Kafka","optional":true},{"name":"Azure","optional":true},{"name":"Azure Data Factory","optional":true},{"name":"Delta Lake","optional":true},{"name":"Docker","optional":true},{"name":"Kubernetes","optional":true},{"name":"Machine Learning","optional":true}],"status":"live","first_seen_at":"2026-11-11T15:59:42Z","employer_posted_date":"2026-11-11","last_verified_at":"2026-11-11T15:59:42Z","board_verified":true,"closed_at":null,"days_open":0,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":0},"description":"Career Category\nStrategy and InnovationJob Description\nRole Summary\nWe’re hiring a Data Engineer with Python backend development experience to build scalable data pipelines and services. The role combines data engineering with backend API development, including integrating data platforms with applications and AI agents.\nThe ideal candidate has hands-on experience with Python, SQL, Databricks, and Apache Spark. They should also understand REST APIs, relational and NoSQL databases, and how to improve Spark workloads for performance and scale.\nKey Responsibilities\nDesign, build, and maintain data ingestion and ETL/ELT pipelines using Python, SQL, Databricks, and Spark/PySpark.\nIntegrate data from APIs, databases, files, and third-party systems.\nDevelop and maintain backend services and REST APIs using Python frameworks such as FastAPI, Flask, or Django.\nBuild API integrations that allow applications and AI agents to access approved data and services.\nDesign and work with relational and NoSQL databases, including schemas, data models, and queries.\nOptimize Spark jobs and Databricks workloads for performance, scalability, and cost.\nApply distributed computing principles to process large datasets reliably.\nImplement data validation, error handling, logging, and monitoring.\nTroubleshoot pipeline, API, and database issues in development and production environments.\nWrite tests and documentation, and participate in Git, code reviews, CI/CD, and deployment workflows.\nCollaborate with data, backend, AI/ML, product, and application teams.\nBasic Qualifications and Experience:\nMaster's OR Bachelor's degree in IT/Computer Science/Engineering. and 12 to 17 years of work experience \nRequired Skills\nStrong Python development skills.\nStrong SQL skills and experience with relational databases.\nHands-on experience with Databricks and Apache Spark/PySpark.\nExperience building data pipelines and integrating data from multiple sources.\nExperience developing or integrating REST APIs.\nWorking knowledge of NoSQL databases. Hands-on experience integrating APIs with AI agents or AI/ML applications.\nUnderstanding of Spark performance optimization, scalability, and distributed systems.\nFamiliarity with Git, testing, debugging, and production support.\nStrong problem-solving and communication skills.\nGood to Have\nExperience with FastAPI, Flask, or Django.\nExperience with Delta Lake, Azure Data Lake, or Azure Data Factory.\nFamiliarity with Airflow, Kafka, Docker, or Kubernetes.\nExperience with authentication and authorization for APIs.\nExperience supporting GenAI or machine learning data pipelines.\nPreferred Candidate Profile\nWe’re looking for someone who can work across the data and backend layers: ingest and transform data, store it in suitable relational or NoSQL systems, and expose it through APIs for applications or AI agents.\nThe candidate should be able to design, build, optimize, test, and support a solution such as:\nSource systems → Databricks/Spark processing → relational or NoSQL storage → Python API → application or AI agent\nEQUAL OPPORTUNITY STATEMENT\nAmgen is an Equal Opportunity employer and will consider you without regard to your race, color, religion, sex, sexual orientation, gender identity, national origin, protected veteran status, or disability status.\nWe will ensure that individuals with disabilities are provided with reasonable accommodation to participate in the job application or interview process, to perform essential job functions, and to receive other benefits and privileges of employment. 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