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Internova Travel GroupPosted 1 month ago

Manager, Data Management

On-siteMontevideo, Montevideo Department, Uruguay

Full TimeSenior LevelMasters DegreeLarge

Job Summary

Lead the architecture, implementation, support, and evolution of enterprise data platforms, including Master Data Management solutions and broader cloud-based data services. Own the technical direction for the MDM platform, covering data models, integration patterns, survivorship rules, matching, workflow, stewardship, and data quality processes. Define and advance the long-term architecture for modern big data platforms, including data lakes, data lakehouses, delta lakes, and scalable storage patterns. Provide leadership and guidance to data engineers and developers in architecture, design, development, deployment, platform operations, and production support activities. Design and oversee integrations between data platforms, operational systems, and analytical platforms using APIs, ETL/ELT pipelines, Azure Data Factory, Function Apps, Logic Apps, and related cloud services. Establish architecture standards and engineering best practices for ingestion, transformation, orchestration, storage, semantic modeling, observability, and security.

Required Qualifications

  • BA/BS or master's degree in Computer Science, Information Systems, Engineering, or a related field
  • 7+ years of progressive experience in data architecture, data engineering, big data platforms, data integration, MDM, or related disciplines
  • 5+ years of experience designing and delivering cloud-based data solutions in Microsoft Azure or comparable cloud platforms
  • Strong experience designing modern enterprise data platforms, including data lakes, data lakehouses, delta lakes, scalable storage patterns, and distributed data processing frameworks
  • Hands-on experience with cloud data technologies such as Azure Data Lake Storage, Azure Databricks, Azure SQL Database, Azure Data Factory, Microsoft Fabric, Snowflake, or comparable services
  • Solid experience in Azure Function Apps, Azure Logic Apps, Azure Kubernetes Service (AKS), and Azure Databricks
  • Strong knowledge of data modeling, data architecture, ETL/ELT design, pipeline orchestration, and batch and streaming integration patterns
  • Experience with Spark-based processing, SQL, Python, or other modern data engineering tools and techniques used to build scalable cloud data platforms
  • Experience building and supporting integrations using APIs, event-driven or file-based data exchange, and operational-to-analytical data movement patterns
  • Working knowledge of Master Data Management concepts and platforms, including data quality, mastering, matching, survivorship, hierarchy management, and stewardship workflows
  • Experience with DevOps and delivery practices using tools such as Azure DevOps, Git repositories, CI/CD pipelines, and Agile delivery methods
  • Understanding of data governance, metadata, lineage, cataloging, quality controls, and security models such as Azure AD and role-based access
  • Proven ability to lead teams, manage multiple initiatives, define architecture direction, and drive delivery in complex enterprise environments
  • Excellent communication and stakeholder management skills, with the ability to translate complex technical concepts into clear business language
  • Self-starter with strong analytical and problem-solving skills and the ability to independently identify root causes, evaluate options, and implement scalable solutions

Desired Qualifications

  • Experience in the travel industry
  • Experience with Master Data Management platforms such as Profisee or comparable tools
  • Microsoft Azure certifications such as Azure Data Engineer Associate, Azure Solutions Architect, or related cloud certifications
  • Experience with data governance and catalog tools such as Microsoft Purview
  • Familiarity with project and work management tools such as Jira, Confluence, and SharePoint
  • Experience managing offshore, remote, or hybrid delivery teams
  • Exposure to machine learning, advanced analytics, AI-enabled data capabilities, or real-time/event-driven data architectures is a plus

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