{"id":3825718,"url":"https://alion.io/job/hitachi-energy-engineering-data-architect","title":"Engineering Data Architect","company":{"id":92953,"name":"Hitachi Energy","domain":"hitachienergy.com","url":"https://alion.io/company/hitachienergy","size_band":"11-50","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":null,"truth_index":null},"role":"Data Science","role_family":"Data Science","seniority":"staff","employment_type":"full_time","work_mode":"hybrid","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Łódź, Poland"],"countries":["PL"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":null,"experience_years_min":5,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Digital Twin","optional":false},{"name":"Knowledge Graph","optional":false},{"name":"Machine Learning","optional":false},{"name":"Master Data Management","optional":false},{"name":"RAG","optional":false},{"name":"Semantic Search","optional":false}],"status":"live","first_seen_at":"2026-11-05T14:07:10Z","employer_posted_date":null,"last_verified_at":"2026-11-05T14:07:10Z","board_verified":false,"closed_at":null,"days_open":2,"trust":{"level":"not_scored","repost_count":null,"flags":[],"days_open":2},"description":"Hitachi Energy is looking for a Engineering Data Architect to define, govern, and evolve the data architecture foundation for global engineering platforms, digital engineering solutions, analytics, and AI-enabled transformation initiatives. The role combines data architecture, engineering platform knowledge, integration architecture, data governance, and AI data readiness to enable trusted, scalable, and reusable data capabilities across the engineering ecosystem.\nThe successful candidate will work at the intersection of Engineering Platforms, Enterprise Architecture, Data Analytics & AI, and software delivery teams. The role will translate business and engineering needs into modern data models, platform integration patterns, governed datasets, analytics capabilities, and AI-ready data products that improve engineering productivity, product lifecycle visibility, platform adoption, and business value realization.\n\nMore about us   \n\nAt Hitachi Energy, we recognize that our people are at the heart of our success. We are committed to providing a supportive and inclusive workplace, competitive rewards, and opportunities for professional and personal growth. Our benefits package is designed to help employees thrive both at work and in their personal lives.\n\nOur benefits offering for this role generally includes:\nPrivate medical care and life insurance\nAccess to fitness and wellness programs\nAccess to benefits platform with discounts and perks\nEmployee Capital Plans (PPK)\nEquipment for working from home or allowances for setting up a workplace at home\nSpectacles and contact lenses allowance\nCompany events and team‑building activities\nPsychological support program\n\nWe are committed to full transparency and compliance with all legal requirements, ensuring that every candidate knows exactly what to expect at each stage of the recruitment process. Once the process is successfully completed, we will share detailed information about financial conditions and benefits with the selected candidate. Before signing the employment contract, you will receive all remaining details of the offer, giving you the time and space to review everything carefully.*\n*Applicable only for Poland location align with local law regulations \nZakres obowiązków\nDefine and maintain the data architecture roadmap for Engineering Platforms, ensuring alignment with enterprise architecture, digital transformation, and data strategy principles.\nDesign canonical and reusable data models related to products, processes, systems, digital twins etc.\nEstablish integration architecture patterns, APIs, event models, data exchange mechanisms, and data services connecting engineering landscape applications, cloud platforms, AI services, analytics platforms, and future digital engineering solutions.\nCreate a trusted data foundation for engineering analytics, executive reporting, platform observability, software delivery performance measurement, and value realization tracking.\nDefine data governance, ownership, stewardship, metadata, reference data, lineage, quality, privacy, security, and compliance standards for engineering and platform data.\nEnable AI and Generative AI use cases by defining AI-ready data products, semantic models, retrieval-augmented generation patterns, knowledge graphs, vector search foundations, training datasets, and governed data access models.\nPartner with platform owners, solution architects, product managers, business analysts, engineering leaders, and Data Analytics & AI teams to translate business requirements into scalable, secure, and maintainable data solutions.\nLead data architecture reviews for projects, demands, business cases, and change requests to ensure consistency, interoperability, reuse, compliance, and long-term platform sustainability.\nDrive continuous improvement of data quality, reporting automation, self-service analytics, and engineering intelligence capabilities across global engineering organizations.\nDevelop architecture standards, blueprints, decision records, reference architectures, and implementation guidance for data platforms, integrations, analytics, and AI-enabled engineering solutions.\nWymagania\nYour background\nMaster’s degree in Computer Science, Information Systems, Data Science, Software Engineering, Engineering, or a related discipline.\n5+ years of experience in data architecture, information architecture, enterprise architecture, solution architecture, data engineering, or related technology roles.\nExperience designing large data models, integration architectures, data platforms, data lakes, data warehouses, or data products in complex global organizations.\nSolid understanding of PLM, ERP, engineering platforms, software delivery ecosystems, cloud data platforms, analytics, and enterprise integration technologies.\nPractical experience with data governance, metadata management, master data management, data quality, security, privacy, compliance, and lifecycle management.\nExperience supporting AI, Machine Learning, Generative AI, semantic search, knowledge management, or advanced analytics initiatives with governed and trusted data foundations.\nExcellent stakeholder management, facilitation, communication, systems thinking, and architecture leadership skills.\nTech stack\nData science\nEnterprise Architect\nData engineering\nData models\nData Lake\nData warehouses\nPLM\nERP\nCloud\nData management\nSecurity\nAI\nMachine Learning\nStakeholder management","description_format":"text","description_chars":5444,"description_truncated":false,"requirements":{"experience_years_min":5,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":null,"security_clearance":false,"languages":[]},"benefits":["Company events","Life insurance","Wellness"],"hiring_locations":[],"hiring_excludes":[],"relocation_offered":false,"industries":["Power Grid","Smart Grid","Electrical Equipment & 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