{"id":3281784,"url":"https://alion.io/job/link-group-data-architect","title":"Data Architect","company":{"id":880,"name":"Link Group","domain":"linkgroup.co","url":"https://alion.io/company/link-group","size_band":"1001-5000","is_staffing_agency":false,"employer_type":"staffing","is_intermediary":false,"listed_via":null,"ats_vendor":"Recruitify","truth_index":{"grade":"B","score":84,"open_postings":97,"ghost_share":0,"stale_share":0.639,"repost_share":0,"time_to_fill_p50_days":47,"computed_at":"2026-10-29T05:49:05Z"}},"role":"Data Science","role_family":"Data Science","seniority":"staff","employment_type":null,"work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Poland"],"countries":["PL"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":68000,"max_usd":115000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":10},"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Airflow","optional":false},{"name":"Azure","optional":false},{"name":"Azure DevOps","optional":false},{"name":"CI/CD","optional":false},{"name":"Databricks","optional":false},{"name":"ETL/ELT","optional":false},{"name":"Microsoft Fabric","optional":false},{"name":"Terraform","optional":false},{"name":"UML","optional":false}],"status":"live","first_seen_at":"2026-10-12T00:00:00Z","employer_posted_date":"2026-10-13","last_verified_at":"2026-10-29T12:55:02Z","board_verified":true,"closed_at":null,"days_open":17,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":17},"description":"Data Architect\nRole Overview\nWe are looking for an experienced Data Architect to shape and evolve an enterprise data platform that enables reliable data integration, advanced analytics, and data-driven business decisions. The role combines architectural design with technical leadership, ensuring that data solutions are scalable, secure, well-documented, and aligned with business needs. You will establish architectural principles and reusable design patterns while collaborating with engineering teams and business stakeholders to support the platform’s long-term development.\nKey Responsibilities\nDesign and evolve the end-to-end data architecture, including data models, ingestion patterns, transformation layers, data products, and consumption interfaces.\nDefine architectural principles and technical standards for data storage, processing, integration, access, and sharing.\nDesign scalable data integration solutions covering batch and streaming workloads, ETL/ELT processes, and connections between source systems and analytical environments.\nEstablish best practices for data modelling, metadata management, data lineage, reference data, and business terminology.\nMaintain architectural documentation, including data models, integration patterns, design decisions, standards, and reference materials.\nTranslate business and technical requirements into architectural designs, data structures, and implementation recommendations.\nConduct architecture reviews, document key decisions, and guide delivery teams in applying agreed standards and security principles.\nWork closely with Data Engineers, Analysts, Data Owners, Project Managers, and business stakeholders to ensure solutions meet organizational requirements.\nPresent architectural recommendations and platform development options to both technical and business audiences.\nRequired Experience and Skills\nProven experience designing and developing scalable enterprise data platforms based on Lakehouse architecture.\nStrong knowledge of Azure Databricks and modern cloud-based data processing environments.\nExperience creating conceptual, logical, and physical data models.\nPractical knowledge of data integration, including ETL/ELT, batch processing, streaming, and data exchange between operational and analytical systems.\nExperience defining architectural standards, reusable patterns, and best practices for data modelling, integration, security, and data access.\nStrong understanding of data architecture principles and the relationship between data platforms, reporting, and analytics.\nData Modelling and Architecture Documentation\nAdvanced knowledge of data modelling techniques, including ERD and UML.\nExperience using Enterprise Architect or comparable tools for documenting data models, architectures, and data flows.\nAbility to manage and maintain an architecture repository containing data models, standards, architectural decisions, integration patterns, and reference documentation.\nTechnology Environment\nMicrosoft Azure cloud ecosystem and services supporting enterprise-scale data platforms.\nAzure Databricks for data engineering and Lakehouse processing.\nAzure Data Lake Storage and Delta format for data storage.\nMicrosoft Fabric for analytics and data consumption.\nApache Airflow for workflow orchestration.\nUnity Catalog for data discovery, access control, schema management, and governance.\nDatabricks Asset Bundles for managing and deploying data workflows.\nDelta Sharing for secure data exchange across environments.\nTerraform and Infrastructure as Code for automating cloud and platform resources.\nAzure DevOps for source control and CI/CD processes.\nNice to Have\nFamiliarity with data management and enterprise architecture frameworks, such as DAMA-DMBOK and TOGAF.","description_format":"text","description_chars":3755,"description_truncated":false,"requirements":{"experience_years_min":null,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":null,"security_clearance":false,"languages":[]},"benefits":[],"hiring_locations":[],"hiring_excludes":[],"relocation_offered":false,"industries":["IT Outsourcing & Dedicated Teams","Managed IT Services (MSP)","IT Staffing & Staff Augmentation"],"lifecycle":[{"event":"open","at":"2026-10-26T16:46:18Z"}],"visa":[],"liveness":{"score":56,"band":"ok","label":"Likely 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