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.
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.
Collaborate with cross-functional teams to understand data requirements and provide support for data-driven initiatives.
Mentor and guide junior members of the team to help them get up to speed in a short amount of time.

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
Ability to scope, estimate, and deliver committed work within deadlines, both independently and as part of an agile team
Excellent communication and influencing skills, especially in regard to data solutions and outcomes
Strong knowledge of how data drives analytical and reporting activities, including automated marketing and personalization capabilities

Data Engineer

Key skills