• Lead the technical execution of the migration from Oracle and Boomi to Azure SQL and Azure Data Factory. • Guide architecture and design decisions across database migration, ETL migration, integration, validation, and deployment activities. • Serve as the main technical point of contact with the client. • Translate client requirements, priorities, and constraints into actionable technical direction for the team. • Coordinate the work of the database migration and ETL / ADF engineers. • Review and validate technical designs, source-to-target mappings, migration approaches, and implementation plans. • Provide hands-on technical guidance and troubleshooting support when needed. • Help resolve complex issues related to data conversion, pipeline design, performance, compatibility, validation, and reconciliation. • Track project timeline, deliverables, dependencies, risks, and open decisions. • Ensure the team is aligned on priorities, scope, quality expectations, and delivery commitments. • Communicate project status, risks, blockers, and key decisions to client stakeholders and internal leadership. • Support planning for testing, production cutover, rollback considerations, and post-migration stabilization. • Ensure technical documentation is created and maintained throughout the engagement. • Promote best practices for data migration, ETL design, security, performance, monitoring, and maintainability.

• Design, build, and maintain scalable and efficient data systems, leveraging big data technologies • Lead the data engineering team and manage the project roadmap, ensuring projects are delivered on time and within budget. • Collaborate with cross-functional teams, including data scientists, software engineers, and business stakeholders, to understand and meet their data needs. • Design and implement data pipelines to ingest, process, and store large and complex data sets, ensuring the reliability and performance of the data systems. • Implement data security and privacy controls, following industry best practices and company policies. • Monitor and optimize the performance of data systems, proactively identifying and resolving bottlenecks and issues. • Stay up-to-date with emerging trends and technologies in the field of data engineering, and evaluate their potential impact on the company. • Mentor and guide junior data engineers, providing technical and professional development opportunities to help them grow in their careers.

• Perform data warehouse architecture or enterprise data architecture at a senior level. • Design and develop data models and ETL specifications. • Conduct data analysis and system design. • Author and monitor standards and policy administration. • Coordinate with vendors and manage relations.

• work as part of the Data & AI Factory team, working with the customer to support their data-ops and AI projects • be involved in designing, building, maintaining and troubleshooting data pipelines, models and transformations • help to build, maintain and troubleshoot data observability solutions to improve data quality • help turn data into valuable business insights, preparing custom solutions optimised for each client • act as a trusted advisor for junior team members • lead by example