Data Engineer/ Architect

The Team
GP Bullhound are in the process of moving into our brand new office in Malaga, located right in the city centre. This role will be reporting into the Chief Technology Officer, currently based in London and relocating to Malaga later in the year.
Your Role
GP Bullhound has been forming the European tech scene for 20 years, having worked with success stories such as Spotify, Avito, Klarna, Slack, and Revolut, and is now helping the technology leaders to build the future.
Your Responsibilities
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 manner.
Responsible for the data modelling that feeds the Data Platform.
Maintain and optimise data pipelines to improve performance and quality, minimising impacts on business.
Effectively communicate plans and progress to both technical and non-technical stakeholders.
Develop and implement the Data roadmap for strategic data sets.
Provide regular and accurate reports of progress to the Project lead where required.
Strong focus on Serverless architecture and full separation of compute and storage.
Experience and Qualifications
Experience of building automated data quality checks and metrics.
Experience creating and/or maintaining production software delivery pipelines using common CI/CD tools (GitHub Actions, Azure DevOps, Jenkins, CircleCI, etc.).
Experience productionising machine learning algorithms.
Experience with Infrastructure as Code (Lakeformation, CloudFormation).
Experience with data reporting and visualisation tools (Power BI, Tableau, Quicksight, Qlik, etc.).
Strong experience in leading AWS cloud data platform transformation.
Strong experience implementing end-to-end data pipeline on AWS with deep knowledge of data engineering techniques across data preparation, ETL, & loading, normalisation, aggregation, warehousing, data lakes, and data governance.
Strong experience with Redshift, Athena, S3, Lambda.
Strong experience developing Data Warehouses.
Practical experience in data architecture and data modelling and Python.
Experience managing the costs of data pipelines.

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