Denodo Self-Service Data Platform Engineer

Experience: 5–8 years Overall Experience: Minimum 4+ years in Data Engineering, Data Management, or Analytics Platforms Denodo Experience: Minimum 2 years Work Arrangement: Onsite Joining: Immediate joiner preferred

Job Summary

We 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.

Key Responsibilities

• Design and develop self-service data products, reusable data services, and virtual views using Denodo.

• Develop and maintain Denodo Virtual DataPort (VDP) views, logical data models, and semantic layers.

• Integrate data from databases, cloud platforms, APIs, ERP systems, and SaaS applications.

• Optimize query performance, caching strategies, and data virtualization architecture.

• Implement data transformation, data quality rules, and data abstraction layers.

• Manage data governance, role-based access control (RBAC), data masking, metadata, data cataloging, and lineage.

• Integrate Denodo with Power BI, Tableau, Qlik, and other BI platforms.

• Monitor platform performance, troubleshoot issues, and support upgrades and releases.

• Prepare technical documentation, data dictionaries, operational procedures, and user training materials.

• Provide Level 2/Level 3 support and collaborate with business and technical teams to improve self-service analytics.

Required Skills and Experience

Must-Have

• Overall Experience: Minimum 4+ years in Data Engineering, Data Management, or Analytics Platforms.

• Denodo Experience: Minimum 2+ years of hands-on experience with the Denodo Data Virtualization Platform.

• Denodo Development: Strong experience with Denodo Virtual DataPort (VDP) and Design Studio, including developing and maintaining virtual views.

• Data Virtualization: Strong understanding of data virtualization architecture, data abstraction, query optimization, caching, and performance tuning.

• SQL and Data Modeling: Proficiency in SQL, advanced query development, logical and semantic data modeling, and ETL/ELT concepts.

• Data Integration: Experience integrating data from multiple sources, including relational databases, cloud platforms, APIs, ERP systems, and SaaS applications.

• Data Governance and Security: Knowledge of RBAC, data masking, metadata management, data cataloging, lineage tracking, and access control.

• BI and Analytics: Experience integrating or supporting BI tools, particularly Power BI, Tableau, or Qlik.

• Data Quality: Understanding of data transformation, validation, data quality rules, and enterprise data management practices.

• Troubleshooting: Ability to monitor, diagnose, and resolve data virtualization and query performance issues.

• Documentation: Ability to prepare technical designs, data dictionaries, operational procedures, and support documentation.

• Soft Skills: Strong analytical, problem-solving, communication, and collaboration skills, with the ability to work with business and technical stakeholders.

Good-to-Have

• Denodo Certification: Denodo Certified Professional or Denodo Certified Developer certification.

• Additional Denodo Tools: Hands-on experience with Denodo Data Catalog, Scheduler, and Solution Manager.

• Cloud Platforms: Experience working with Microsoft Azure, AWS, or Google Cloud Platform (GCP).

• Modern Data Technologies: Exposure to Azure Data Factory, Databricks, Azure Synapse Analytics, or Snowflake.

• Database Technologies: Experience with Oracle, SQL Server, PostgreSQL, MySQL, Azure SQL, or Amazon Redshift.

• API Integration: Familiarity with REST/SOAP APIs and enterprise data integration patterns.

• Advanced Analytics: Experience with SAP Analytics Cloud or other enterprise analytics platforms.

• Data Architecture: Understanding of Data Mesh and Data Fabric architectures.

• Governance Solutions: Exposure to enterprise data governance and data catalog solutions.

• Delivery Methodologies: Experience with Agile, Scrum, and DevOps methodologies.

• Self-Service Analytics: Experience implementing enterprise-wide self-service data and analytics solutions across cloud and on-premises environments.

• Stakeholder Enablement: Experience delivering user training, knowledge transfer, and technical guidance to business users and analysts.

Key Deliverables

• Reusable Denodo virtual views, datasets, and data services.

• Optimized and scalable data virtualization solutions.

• Secure and governed enterprise data access.

• Data catalog, metadata, and lineage documentation.

• Improved data accessibility and reporting efficiency.

• Increased adoption of self-service analytics capabilities.