{"id":3512392,"url":"https://alion.io/job/siemens-senior-data-engineer-2","title":"Senior Data Engineer","company":{"id":131,"name":"Siemens","domain":"siemens.com","url":"https://alion.io/company/siemens","size_band":"1001-5000","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Avature","truth_index":{"grade":"A","score":100,"open_postings":18,"ghost_share":0,"stale_share":0,"repost_share":0,"time_to_fill_p50_days":11,"computed_at":"2026-11-02T06:13:15Z"}},"role":"Data Science","role_family":"Data Science","seniority":"senior","employment_type":null,"work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Gurgaon, India"],"countries":["IN"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":21000,"max_usd":45000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":75},"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AWS","optional":false},{"name":"Git","optional":false},{"name":"Snowflake","optional":false},{"name":"SQL","optional":false}],"status":"live","first_seen_at":"2026-10-30T08:30:25Z","employer_posted_date":"2026-10-30","last_verified_at":"2026-11-02T04:25:14Z","board_verified":true,"closed_at":null,"days_open":2,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":2},"description":"A Snapshot of Your Day\nAs a Senior Data Engineer, you will build the trusted data foundation that enables analytics, AI and data-driven business decisions across Siemens Energy.\nWorking within a complex and distributed system landscape, you will discover, analyse and integrate data from multiple business domains and applications. Your focus will be on transforming fragmented data into governed, reusable and scalable data products that can be leveraged across the organisation.\nYou will collaborate with business stakeholders, Data & AI consultants and analytics teams to understand data requirements, explore source systems and translate business concepts into sustainable data models. Whether identifying untapped data sources, designing reusable data products or engineering scalable solutions in Snowflake, your work will help establish the foundation for future analytics, AI and business solutions.\nHow You'll Make an Impact\nBuild and evolve the Snowflake-based data platform as the foundation for analytics, AI and business solutions.\nExplore and understand complex business processes, source systems and data landscapes to identify valuable data assets.\nTransform fragmented data into trusted, reusable and governed data products that can be leveraged across multiple business domains.\nDesign and maintain scalable data models that create a common understanding of key business entities and processes.\nDevelop and operate reliable data pipelines that ensure high-quality and timely data availability.\nBuild and maintain reusable data products covering domains such as Assets, Offers, Orders, Projects, Service Plans, CSC and FS360.\nEstablish engineering standards, reusable frameworks and best practices that improve scalability, maintainability and reliability.\nCollaborate with business and Data & AI teams to translate business requirements into sustainable and scalable data solutions.\nEnsure platform reliability, performance, data quality and operational excellence.\nWhat You Bring\nA university degree in Computer Science, Data Engineering, Information Systems, Software Engineering or a related field.\nSeveral years of experience in data engineering, analytics engineering or modern cloud-based data platforms.\nStrong expertise in Snowflake or comparable cloud data platforms.\nStrong SQL and data modelling skills with experience designing scalable and reusable data structures.\nExperience exploring, integrating and engineering data across complex enterprise landscapes and multiple source systems.\nA solid understanding of data architecture, data governance and modern data engineering principles.\nExperience building reusable data products, data pipelines and scalable analytical foundations.\nA structured and analytical mindset with the curiosity to investigate unfamiliar systems, discover valuable data assets and solve complex data challenges.\nThe ability to translate business concepts into scalable data models and technical solutions.\nExperience with cloud technologies such as AWS is an advantage.\nExperience working with enterprise data from platforms such as Salesforce, SAP, Teamcenter or similar business systems is an advantage.\nExperience with version control systems such as Git and modern software engineering practices is an advantage.\nA proactive and ownership-oriented mindset with a passion for building reliable data foundations that create long-term business value.\nStrong communication skills and the ability to work effectively with both business and technical stakeholders.\nAdvanced English proficiency and the ability to work effectively in a global 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