• Develop, maintain, and monitor data ingestion and enrich ETL/ELT pipelines within the platform that load and convert raw data into data products. • Partner with regional and/or global IT infrastructure teams to support and configure data platform storage and compute layers. • Maintain and build CI/CD pipeline code and automated test plans to ensure automated deployment between development and production environments. • Manage data platforms related to ITSM ticketing processes (incident & change requests). • Collaborate with data team members, architects, data stewards, data owners, and business SMEs to develop data product business requirements for data cleansing and enrichment. • Implement data security and data governance policies within the data platform to protect sensitive information and maintain data quality. • Partner with cybersecurity and compliance teams to rigorously ensure compliance with applicable data security, data protection, and regulation requirements. • Partner with global data teams to ensure that the local data platform & products maintain interoperability. • Continuously identify and drive opportunities to improve platform performance, reduce complexity and technical debt and reduce cloud computing and storage costs. • Maintain support documentation within the team repository. • Escalate data platform issues to the attention of management / appropriate partners. • Leverage agile frameworks and Azure DevOps to execute the team backlog. • Implement data platform metadata management standards and policies.

• Design and build our data warehouse • Build ETL/ELT pipelines • Take full ownership of the data structure and handling • Take care of our internal dashboard used by several departments at Relai • Implement internal features of the dashboard such as performing actions related to users or transactions • Implement the back-end endpoints related to these actions

• Design, develop, and maintain data pipelines and datastores that support enterprise analytics, data science, and operational workloads. • Lead and support large-scale database migration initiatives, including on-premises to cloud migrations. • Monitor, analyze, and optimize the performance and stability of data layer services and platforms. • Ensure data integrity, quality, and compliance across pipelines and datasets. • Collaborate closely with peers across engineering, analytics, and technology teams. • Guide, coach, and mentor data engineers, BI developers, and analysts. • Design and implement enterprise-scale data solutions with long-term business impact. • Build and maintain data processing solutions using Python and/or Scala. • Work with a variety of data ingestion patterns, including SFTP, APIs, streaming, and batch processing. • Design and support database models optimized for analytical and reporting use cases. • Implement monitoring, alerting, and observability for data pipelines and infrastructure. • Maintain clear and comprehensive documentation of data architectures, pipelines, and processes. • Work within an Agile environment, collaborating through tools such as Jira and Git.

• Maintain and optimize cloud infrastructure to ensure reliability and scalability for data systems. • Extract, transform, and load (ETL) data across various systems to support business operations and decision-making. • Identify and resolve issues within existing systems to enhance performance, stability, and scalability. • Troubleshoot and fix bugs in deployed systems, ensuring minimal downtime and disruption. • Optimize systems and streamline existing processes to improve efficiency and reduce latency. • Build and optimize system deployment structures to ensure smooth, consistent deployments and system performance.