Data Management Manager

About the role

Internova Travel Group is seeking a Data Management Manager to lead the architecture, design, delivery, and evolution of its enterprise data platforms. This senior position will drive the company’s modern data strategy, with a focus on Master Data Management (MDM) and Azure‑based big‑data solutions.

Key responsibilities

• Define and own the technical direction for MDM, including data models, integration patterns, survivorship rules, matching, workflow, stewardship, and data‑quality processes.
• Design, implement, and evolve cloud‑native data platforms such as data lakes, lakehouses, delta lakes, and scalable storage patterns on Azure.
• Lead a team of in‑house and outsourced data engineers and developers through architecture, requirements, design, development, deployment, and production support.
• Build and maintain integrations between data platforms, operational systems, and analytical solutions using APIs, ETL/ELT pipelines, Azure Data Factory, Function Apps, Logic Apps, and related services.
• Establish architecture standards and engineering best practices for ingestion, transformation, orchestration, storage, semantic modeling, observability, and security.

Required profile

• Bachelor’s or master’s degree in Computer Science, Information Systems, Engineering, or a related field.
• 7+ years of progressive experience in data platform architecture, big‑data technologies, and cloud deployments.
• Proven leadership experience managing data engineering teams and delivering enterprise‑scale data solutions.

Required skills

• Microsoft Azure (including Azure Data Factory, Function Apps, Logic Apps)
• Master Data Management (MDM) concepts and tools
• Big Data technologies and frameworks
• Data Lakes, Delta Lakes, Data Lakehouse architectures
• ETL/ELT pipeline design and implementation
• API design and integration
• Data modeling, integration patterns, survivorship rules, matching, workflow, and data‑quality processes
• Cloud‑native data processing frameworks and scalable storage patterns