Role responsibilities: Design and implement data models that align with business requirements and support efficient querying and analysis. Design, develop and maintain data pipelines that extract, load and transform data from various sources into the data warehouses. Ensure the pipelines are reliable, scalable, and efficient, considering factors including data volume, velocity, and variety. Implement data quality checks and validation processes to maintain accurate and reliable data. Set up monitoring and alerting to proactively identify and resolve issues. Perform root cause analysis for incidents and implement corrective actions. Contribute to the technical design and vision for the data platform. Employee responsibilities: Collaborate with cross-functional teams, including product managers, data scientists, analysts, and business stakeholders to understand data requirements and deliver solutions that meet business needs. Communicate technical concepts and solutions effectively to non-technical stakeholders. Stay updated with emerging data engineering technologies and trends, and evaluate their potential benefits for the organisation's data ecosystem. Qualifications, Experience & Skills Essential qualifications, experience & skills Fluent in at least one programming language (Python). Proficient in SQL Understanding of OLTP concepts including normalised schema design. Understanding of OLAP concepts and data model design. Experience leading the designing and building data pipelines, ETL processes, and managing data infrastructure using a tool such as DBT Experience leading workflows automation, and managing task dependencies using a tool like Apache Airflow. Problem-Solving & Leadership: A strong analytical mindset, a passion for tackling complex technical challenges, and the ability to find creative solutions issues. Excellent communication and interpersonal skills, with the ability to lead technical discussions, build consensus, and work effectively with cross-functional teams. Deep understanding of cloud migration strategies, best practices, and potential pitfalls. Desirable qualifications, experience & skills Experience with Google Cloud Platform, AWS or Azure including services for data storage, processing, and analytics. Experience with cloud deployment and test automation using a CI/CD solution such as Cloud Build or Concourse Experience in deploying cloud infrastructure as code (IaC) using Terraform or similar Show more Show less