Data Engineering Practice Lead

Data Engineering & Platform Enablement

Required

Skills & Experience:

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
-Databricks Data Engineer Professional
-Azure Data Engineer Associate
-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 Data Ops, 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.

Job Description:

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.

Key responsibilities include:

Data Platform Strategy & Enablement:

• Lead the design, implementation, and evolution of the Databricks-based technology reference data platform.
• Develop platform standards, engineering patterns, and operating procedures that support enterprise scalability and sustainability.
• Establish a modern data ecosystem capable of supporting governance, reporting, analytics, and AI-driven use cases.
• Drive platform modernization initiatives that improve performance, automation, resilience, and user experience.

Data Ingestion & System Onboarding:

• Lead onboarding of technology systems of record into the enterprise data platform.
• Design and implement scalable integration patterns including APIs, event-driven architectures, data streaming, and zero-copy data sharing.
• Establish standards for source system connectivity, transformation, validation, and data movement.
• Partner with source system owners to ensure data is delivered accurately, securely, and efficiently.

Data Engineering & Transformation:

• Design, build, and manage data pipelines that transform disparate source data into standardized enterprise data assets.
• Develop reusable ingestion and transformation frameworks that accelerate onboarding of new data sources.
• Implement automated controls to ensure data quality, integrity, completeness, and consistency.
• Optimize data processing and storage solutions to support large-scale technology data domains.

Data Operations & Reliability:

• Establish monitoring and observability capabilities to ensure platform health and data reliability.
• Define operational support processes, service-level agreements, and issue management procedures.
• Lead remediation efforts for data delivery issues, performance bottlenecks, and platform incidents.
• Ensure platform availability, resiliency, and business continuity requirements are met.

Data Security, Controls & Compliance:

• Ensure compliance with enterprise security, data protection, and regulatory requirements.
• Implement access controls, encryption standards, audit logging, and monitoring capabilities.
• Partner with Risk, Security, and Compliance teams to support governance objectives.
• Ensure adherence to enterprise technology and data management standards.

Enablement of Data Products:

• Support development and operationalization of technology data products.
• Ensure data products are sourced from authoritative systems and delivered through governed engineering processes.
• Build reusable data services supporting reporting,…