{"id":3335309,"url":"https://alion.io/job/amgen-associate-data-engineer-3","title":"Associate 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":344,"ghost_share":0,"stale_share":0.576,"repost_share":0.012,"time_to_fill_p50_days":43,"computed_at":"2026-11-02T06:13:15Z"}},"role":"Data Science","role_family":"Data Science","seniority":"junior","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":14500,"max_usd":34000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":12},"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Apache Kafka","optional":false},{"name":"AWS","optional":false},{"name":"Databricks","optional":false},{"name":"ETL/ELT","optional":false},{"name":"Hadoop","optional":false},{"name":"MySQL","optional":false},{"name":"PostgreSQL","optional":false},{"name":"pySpark","optional":false},{"name":"Python","optional":false},{"name":"Scala","optional":false},{"name":"Spark","optional":false},{"name":"SQL","optional":false},{"name":"Amazon EC2","optional":true},{"name":"Amazon EKS","optional":true},{"name":"Amazon Redshift","optional":true},{"name":"Amazon S3","optional":true},{"name":"AWS Lambda","optional":true},{"name":"Kubernetes","optional":true},{"name":"Machine Learning","optional":true}],"status":"live","first_seen_at":"2026-09-11T00:00:00Z","employer_posted_date":"2026-09-11","last_verified_at":"2026-11-02T01:01:50Z","board_verified":true,"closed_at":null,"days_open":52,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":52},"description":"Career Category\nInformation SystemsJob Description\nRole Description:\nThe role is responsible for designing, building, maintaining, analyzing, and interpreting data to provide actionable insights that drive business decisions. This role involves working with large datasets, developing reports, supporting and executing data governance initiatives and, visualizing data to ensure data is accessible, reliable, and efficiently managed. The ideal candidate has strong technical skills, experience with big data technologies, and a deep understanding of data architecture and ETL processes\nRoles & Responsibilities:\nDesign, develop, and maintain data solutions for data generation, collection, and processing\n\nBe a key team member that assists in design and development of the data pipeline\n\nCreate data pipelines and ensure data quality by implementing ETL processes to migrate and deploy data across systems\n\nContribute to the design, development, and implementation of data pipelines, ETL/ELT processes, and data integration solutions\n\nTake ownership of data pipeline projects from inception to deployment, manage scope, timelines, and risks\n\nCollaborate with cross-functional teams to understand data requirements and design solutions that meet business needs\n\nDevelop and maintain data models, data dictionaries, and other documentation to ensure data accuracy and consistency\n\nImplement data security and privacy measures to protect sensitive data\n\nVery good understanding of Databricks\n\nLeverage cloud platforms (AWS preferred) to build scalable and efficient data solutions\n\nCollaborate and communicate effectively with product teams\n\nCollaborate with Data Architects, Business SMEs, and Data Scientists to design and develop end-to-end data pipelines to meet fast paced business needs across geographic regions\n\nIdentify and resolve complex data-related challenges\n\nAdhere to best practices for coding, testing, and designing reusable code/component\n\nExplore new tools and technologies that will help to improve ETL platform performance\n\nParticipate in sprint planning meetings and provide estimations on technical implementation\n\nBasic Qualifications and Experience:\nBachelor’s degree and 2 to 4 years of Computer Science, IT or related field experience\n\nFunctional Skills:\nMust-Have Skills\nProficiency in Databricks ,Python, PySpark, and Scala for data processing and ETL (Extract, 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