{"id":3280386,"url":"https://alion.io/job/datamatics-technologies-denodo-self-service-data-platform-engineer-datamatics-technologies-2","title":"Denodo Self-Service Data Platform Engineer - Datamatics Technologies","company":{"id":4413925,"name":"Datamatics Technologies","domain":"datamaticstechnologies.com","url":"https://alion.io/company/datamaticstechnologies","size_band":"201-500","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"JazzHR","truth_index":null},"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":["Riyadh, Saudi Arabia"],"countries":["SA"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":41000,"max_usd":107000,"period":"year","method":"global_role_cell_scaled_by_country","sample_n":2679},"experience_years_min":5,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"ETL/ELT","optional":false},{"name":"Power BI","optional":false},{"name":"SQL","optional":false},{"name":"Tableau","optional":false},{"name":"Agile","optional":true},{"name":"Amazon Redshift","optional":true},{"name":"AWS","optional":true},{"name":"Azure","optional":true},{"name":"Azure Data Factory","optional":true},{"name":"Azure SQL Database","optional":true},{"name":"Databricks","optional":true},{"name":"GCP","optional":true},{"name":"MySQL","optional":true},{"name":"Oracle","optional":true},{"name":"PostgreSQL","optional":true},{"name":"Rest API","optional":true},{"name":"Scrum","optional":true},{"name":"Snowflake","optional":true},{"name":"SOAP","optional":true}],"status":"live","first_seen_at":"2026-10-26T16:11:46Z","employer_posted_date":"2026-10-26","last_verified_at":"2026-10-28T11:08:17Z","board_verified":true,"closed_at":null,"days_open":1,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":1},"description":"Experience: 5-8 years\nOverall Experience: Minimum 4+ years in Data Engineering, Data Management, or Analytics Platforms\nDenodo Experience: Minimum 2 years\nWork Arrangement: Onsite\nJoining: Immediate joiner preferred\nJob Summary\nWe are looking for an experienced Denodo Self-Service Data Platform Engineer to design, develop, and support enterprise data virtualization solutions. The candidate will enable business users and analysts to access trusted, secure, and governed data through scalable self-service analytics platforms.\nKey Responsibilities\nDesign and develop self-service data products, reusable data services, and virtual views using Denodo.\n\nDevelop and maintain Denodo Virtual DataPort (VDP) views, logical data models, and semantic layers.\n\nIntegrate data from databases, cloud platforms, APIs, ERP systems, and SaaS applications.\n\nOptimize query performance, caching strategies, and data virtualization architecture.\n\nImplement data transformation, data quality rules, and data abstraction layers.\n\nManage data governance, role-based access control (RBAC), data masking, metadata, data cataloging, and lineage.\n\nIntegrate Denodo with Power BI, Tableau, Qlik, and other BI platforms.\n\nMonitor platform performance, troubleshoot issues, and support upgrades and releases.\n\nPrepare technical documentation, data dictionaries, operational procedures, and user training materials.\n\nProvide Level 2/Level 3 support and collaborate with business and technical teams to improve self-service analytics.\n\nRequired Skills and Experience\nMust-Have\nOverall Experience: Minimum 4+ years in Data Engineering, Data Management, or Analytics Platforms.\n\nDenodo Experience: Minimum 2+ years of hands-on experience with the Denodo Data Virtualization Platform.\n\nDenodo Development: Strong experience with Denodo Virtual DataPort (VDP) and Design Studio, including developing and maintaining virtual views.\n\nData Virtualization: Strong understanding of data virtualization architecture, data abstraction, query optimization, caching, and performance tuning.\n\nSQL and Data Modeling: Proficiency in SQL, advanced query development, logical and semantic data modeling, and ETL/ELT concepts.\n\nData Integration: Experience integrating data from multiple sources, including relational databases, cloud platforms, APIs, ERP systems, and SaaS applications.\n\nData Governance and Security: Knowledge of RBAC, data masking, metadata management, data cataloging, lineage tracking, and access control.\n\nBI and Analytics: Experience integrating or supporting BI tools, particularly Power BI, Tableau, or Qlik.\n\nData Quality: Understanding of data transformation, validation, data quality rules, and enterprise data management practices.\n\nTroubleshooting: Ability to monitor, diagnose, and resolve data virtualization and query performance issues.\n\nDocumentation: Ability to prepare technical designs, data dictionaries, operational procedures, and support documentation.\n\nSoft Skills: Strong analytical, problem-solving, communication, and collaboration skills, with the ability to work with business and technical stakeholders.\n\nGood-to-Have\nDenodo Certification: Denodo Certified Professional or Denodo Certified Developer certification.\n\nAdditional Denodo Tools: Hands-on experience with Denodo Data Catalog, Scheduler, and Solution Manager.\n\nCloud Platforms: Experience working with Microsoft Azure, AWS, or Google Cloud Platform (GCP).\n\nModern Data Technologies: Exposure to Azure Data Factory, Databricks, Azure Synapse Analytics, or Snowflake.\n\nDatabase Technologies: Experience with Oracle, SQL Server, PostgreSQL, MySQL, Azure SQL, or Amazon Redshift.\n\nAPI Integration: Familiarity with REST/SOAP APIs and enterprise data integration patterns.\n\nAdvanced Analytics: Experience with SAP Analytics Cloud or other enterprise analytics platforms.\n\nData Architecture: Understanding of Data Mesh and Data Fabric architectures.\n\nGovernance Solutions: Exposure to enterprise data governance and data catalog solutions.\n\nDelivery Methodologies: Experience with Agile, Scrum, and DevOps methodologies.\n\nSelf-Service Analytics: Experience implementing enterprise-wide self-service data and analytics solutions across cloud and on-premises environments.\n\nStakeholder Enablement: Experience delivering user training, knowledge transfer, and technical guidance to business users and analysts.\n\nKey Deliverables\nReusable Denodo virtual views, datasets, and data services.\n\nOptimized and scalable data virtualization solutions.\n\nSecure and governed enterprise data access.\n\nData catalog, metadata, and lineage documentation.\n\nImproved data accessibility and reporting efficiency.\n\nIncreased adoption of self-service analytics capabilities.","description_format":"text","description_chars":4711,"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":[],"hiring_locations":[],"hiring_excludes":[],"relocation_offered":false,"industries":["Data & Analytics","Information Technology","IT Staffing & Staff Augmentation","Analytics & BI 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