Data Engineering Lead

Collaboration:  Work closely with a cross-functional agile team to deliver high-quality data solutions. Work closely with data analysts, data scientists, and other stakeholders to understand business requirements and translate them into technical solutions. Team leadership Mentor and guide a team of data engineers and analytic engineers (local and offshore), fostering a culture of innovation, collaboration, and engineering excellence. Data Engineering Data pipeline development, maintenance and engineering support with modern data stack in a rapid, agile development practices Cloud data warehouse – development, testing and production deployments; Python, Databricks, Snowflake SQL and administration (mandatory), dbt (mandatory), Airflow (mandatory), Kafka (desirable), Segment (desirable), Terraform (desirable) AWS fundamentals (mandatory), Buildkite (or equivalent CI/CD platform)Lead the development and management of PowerBl semantic models, ensuring strong governance, repeatability, and scalability. Provide standards, guidelines and collaborate in design of logical data modelling and the implementation of physical data models into the platform to ensure consistency, interoperability, maintainability and efficiency. Platform ownership and optimization: Management of data platform budget, ensuring optimisation of costs and vendor management Optimize data pipelines, build pipelines & BI solutions for performance and scalability. Implement data engineering best practices, design, testing, documentation and maintenance Management of the data platform access processes, security access controls, role & attribute access controls and data security controls in collaboration with Cyber and Platform infrastructure teams to ensure that the platform is secure by design. Management and provisioning of AI and BI services on the data platform Data Governance: Ensure compliance with data governance policies and procedures. Monitor data quality and address any issues related to data completeness and accuracy. Collaboration: Provide input to solution design & technical support of pipelines. Documentation: Maintain comprehensive documentation of data engineering solutions, data models, and processes. Contribute to design guides and training materials as needed. Issue and Incident Resolution: Provide support for issue and incident resolution.