Senior Data Engineer

• University or Graduate / post graduate degree in Data Management or related Computer Science or Engineering discipline; or equivalent practical experience
• 10+ years of relevant experience in field of specialization
• AWS Data Analytics or Data Engineering Certification
• Google Professional Data Engineer
• Snowflake, Kafka, or Streaming Technology Certifications
• ITIL Foundation
• Experience in data engineering, data platform delivery, software engineering, cloud data platforms, or related technology roles.
• Experience leading engineering or platform teams in large enterprise environments.
• Proven experience designing and implementing enterprise data lakes, data fabrics, or cloud-native data platforms such as Databricks.
• Strong experience building APIs, event-driven architectures, streaming platforms, and modern integration solutions.
• Hands-on experience developing scalable ETL/ELT pipelines and data transformation frameworks.
• Experience with cloud ecosystems including Azure, AWS, or Google Cloud.
• Strong understanding of DataOps, observability, monitoring, automation, and platform operations.
• Experience supporting enterprise reporting, analytics, AI, and machine learning use cases through modern data platforms.
• Experience working in highly regulated organizations with strong governance, security, and compliance requirements.
• Excellent stakeholder management, communication, and leadership skills.

Day-to-Day:

The Data Engineering & Platform Enablement role is responsible for designing, building, and operating the enterprise technology reference data platform that serves as the foundation for technology governance, reporting, analytics, metrics, and decision-making. Reporting to the Head of Technology Data Management, this role leads the onboarding, integration, transformation, and delivery of technology data from infrastructure, cyber, cloud, AI, and enterprise systems into a Databricks-based data fabric.

The role is accountable for establishing scalable data ingestion patterns, integration frameworks, platform engineering standards, and operational controls that ensure technology data is accurate, accessible, reliable, secure, and consumable. This position plays a critical leadership role in enabling enterprise-wide data products, dashboards, KPIs, risk reporting, and operational insights through modern data engineering and platform capabilities.