Data Architect/ Manager (Azure Databricks)

A leading aviation services organization is seeking a Data Architect / Manager (Azure Databricks) to drive the ongoing development and modernization of its enterprise data platform.

This role focuses on the design, development, and management of end-to-end data solutions, including modern cloud data platforms and emerging AI/GenAI capabilities. The successful candidate will work closely with business, analytics, and technology teams to deliver scalable, high-quality data platforms while ensuring performance, reliability, and governance.

The position requires a strong balance of hands-on data engineering expertise and architectural leadership capability, with solid experience in cloud-native data platforms, data governance, and advanced analytics frameworks.

Key responsibilities:

• Act as a key contributor in the design and delivery of enterprise data platform solutions, partnering with business stakeholders to translate requirements into effective data architectures, pipelines, and data products.
• Design, build, and maintain scalable data platforms using Azure technologies (e.g., Azure Databricks, Azure Data Factory, Data Lake), ensuring high performance, scalability, and reliability.
• Support end-to-end delivery lifecycle, including data architecture, engineering, testing, and deployment, ensuring alignment with business objectives and technical standards.
• Collaborate with cross-functional teams, including analytics, business units, and offshore engineering teams, to ensure smooth implementation and quality delivery.
• Drive development of data pipelines, real-time processing, and integration frameworks, enabling seamless connectivity across enterprise systems.
• Champion data innovation initiatives, including AI/GenAI use cases, advanced analytics, and data product development to unlock business value.
• Administer and enhance data governance practices, including data quality, lineage, metadata management, and regulatory compliance.
• Identify opportunities for continuous improvement and platform modernization, including automation, DevOps, and adoption of cloud-native technologies.
• Ensure platform stability through proactive monitoring, troubleshooting, and root cause analysis of data and system issues.
• Maintain proper documentation, including data models, architecture designs, and technical specifications throughout the delivery lifecycle.

Candidate profile:

• Degree in Computer Science, Information Technology, or a related discipline.
• Minimum 8–12 years of experience in data engineering, data platform management, or data architecture within cloud environments.
• Strong expertise in Azure data ecosystem (e.g., Azure Databricks, Data Factory, Data Lake), with hands-on experience in building scalable data pipelines.
• Solid experience in data modeling, integration frameworks, and enterprise data architecture design.
• Exposure to AI/ML or GenAI technologies is highly preferred, with experience supporting advanced analytics or AI-driven solutions.
• Experience in delivering enterprise-scale or business-critical data platforms.
• Familiarity with real-time data processing (e.g., Kafka, CDC, streaming frameworks) is an advantage.
• Strong analytical and problem-solving skills, with the ability to manage complex data ecosystems.
• Good stakeholder management and communication skills, with the ability to work effectively across business and IT teams.

About the organization:

A well-established aviation services organization with a global presence, undergoing continuous transformation of its data platforms and digital capabilities. The organization is focused on leveraging data, analytics, and emerging AI/GenAI technologies to enhance operational efficiency and business performance.

Operating in a complex and regulated environment, the company emphasizes scalability, reliability, and innovation while investing in modern cloud data platforms and next-generation technologies.

Keywords:

Data Architect, Data Platform Manager, Azure Databricks, Azure Data Factory, Data Lake, Data Architecture, Data Engineering, AI, GenAI, Machine Learning, Data Pipelines, Streaming, Cloud, Digital Transformation, DevOps, Aviation Technology