Data Engineer

Python, PySpark, Terraform or Cloud Formation, SQL, Kafka/ Kenesis, Airflow, AWS.

• Design, develop, and maintain data pipelines for collecting, transforming, and loading data into various data stores.
• Build and maintain data warehousing and data lake solutions
• Develop and deploy data models that support various business requirements
• Write efficient and scalable code in languages such as Python, Scala, or Java
• Lead the design of data solutions with quality, automation, and performance in mind
• Own the data pipelines feeding into the Data Platform ensuring they are reliable and scalable
• Ensure data is available in a fit-for-purpose and timely manner for business and analytics consumption
• Work with Data Governance team to ensure solutions are compliant with regulations such as GDPR and CISO policies and data quality is baked-in to pipelines
• Maintain and optimise existing data pipelines to improve performance and quality, minimising impacts to business
• Collaborate with cross-functional teams to understand data requirements and provide support for data-driven initiatives
• Set and embed standards for systems and solutions, and share knowledge to keep the team engaged and skilled in the latest technology
• Prototype and adopt new approaches, driving innovation into the solutions
• Work closely with the Data Product Manager to support alignment of requirements and sources of data from line of business systems and other endpoints
• Effectively communicate plans and progress to both technical and non-technical stakeholders
• Develop and implement the Data roadmap for strategic data sets
• Communicate complex solutions in a clear and understandable way to both experts and nonexperts
• Mentor and guide junior members of the team to help them get up to speed in a short amount of time
• Interact with stakeholders and clients to understand their data requirements and provide solutions
• Stay up-to-date with industry trends and technology advancements in data engineering
• Promote the Data Platform and Data & Analytics team brand throughout the business and represent the interests of data engineering in cross-functional forums
• Champion the importance of modern data solutions across the business and support the education of colleagues on the business value of obtaining good quality data
• Extensive experience leading AWS and cloud data platform transformations

• Proven track record of delivering large-scale data and analytical solutions in a cloud environment
• Hands-on experience with end-to-end data pipeline implementation on AWS, including data preparation, extraction, transformation & loading, normalization, aggregation, warehousing, data lakes, and data governance
• Expertise in developing Data Warehouses
• In-depth understanding of modern data architecture such as Data Lake, Data Warehouse, Lakehouse, and Data Mesh
• Strong knowledge of data architecture and data modelling practices
• Cost-effective management of data pipelines
• Familiarity with CI/CD driven data pipeline and infrastructure
• Agile delivery approach using Scrum and Kanban methodologies
• Ability to scope, estimate, and deliver committed work within deadlines, both independently and as part of an agile team
• Supporting QA and user acceptance testing processes
• Innovative problem-solving skills and ability to provide clear recommendations
• Understanding of the impact of changes to business rules on data processes
• Excellent communication and influencing skills, especially in regard to data solutions and outcomes
• Experience managing and leading a small team of data engineers
• Self-driven and constantly seeking opportunities to improve data processes.

Strong knowledge of how data drives analytical and reporting activities, including automated marketing and personalization capabilities.