Senior Data Engineer

As a Senior Data Engineer reporting to the Head of Data & Analytics, you will lead and mentor a team of Data Engineers, ensuring the delivery of robust, scalable, and secure data platforms and pipelines. You will be hands-on with architecture and engineering solutions while driving best practices, innovation, and continuous improvement across the data engineering function., * Lead the design, development, and maintenance of scalable data architecture and engineering solutions.

• Manage and mentor a team of Data Engineers, providing technical guidance, coaching, and performance feedback.
• Oversee the delivery of high-quality data pipelines, ensuring reliability, efficiency, and alignment with business needs.
• Define and enforce best practices in data engineering, including coding standards, documentation, and testing.
• Collaborate with cross-functional teams to translate business requirements into robust data solutions.
• Ensure data governance, security, and compliance standards are embedded across all engineering activities.
• Drive continuous improvement in data infrastructure, tooling, and automation.
• Monitor and optimise system performance, proactively identifying and resolving bottlenecks or issues.
• Evaluate and recommend new technologies, frameworks, and tools to enhance the data platform.
• Own the roadmap for data engineering initiatives, ensuring alignment with strategic priorities and resource planning.
• Foster a culture of innovation, collaboration, and accountability within the data engineering team

• Bachelor's degree in Computer Science, Data Engineering, Information Systems, or a related technical field.
• Experience designing, building, and maintaining scalable data pipelines and ETL/ELT processes.
• Hands-on experience with cloud platforms (e.g., Azure, AWS, GCP) and cloud-native data services.
• Proficiency in SQL and one or more programming languages (e.g., Python, Scala, Java).
• Experience with data warehousing solutions (e.g., Snowflake, BigQuery, Redshift).
• Familiarity with version control systems (e.g., Git) and CI/CD practices.
• Prior experience working in cross-functional teams and agile environments.
• Exposure to real-time data streaming technologies (e.g., Kafka, Spark) is desirable.
• Experience leading data engineers or contributing to team development is a plus.
• Exposure to ML engineering workflows and MLOps
• Experience shaping data engineering strategy
• Knowledge of infrastructure-as-code (Terraform, Kubernetes, Docker)