Are you passionate about the intersection of data engineering and machine learning? Do you thrive on solving complex problems and transforming raw data into actionable insights? We’re looking for a talented Machine Learning-focused Data Engineer to join our remote team and play a crucial role in shaping the future of our data infrastructure.
Job Description
- Develop and implement portfolio Data modelling, assurance and utilisation strategies and frameworks that align with enterprise approved governance, data and technology strategy and the Data COE. Lead the implementation of these strategies within the portfolio.
- Design and implement scalable and robust processes for ingesting and transforming complex datasets.
- Contribute to the development of architectural frameworks, apply architecture principles, and drive the development of data architecture models within the organisation.
- Design and develop data models using dimensional modelling and data vault techniques and ensure stated business requirements are met by these models.
- Architect, train, validate and test advanced analytics / machine learning models, using enterprise-grade software engineering practices.
- Design, develops and maintain automated scalable data pipelines that improve estate performance, stability and auditability. These include data pipelines for ETL processing. Monitor and troubleshoot data pipeline issues.
Key Skills & Qualifications
- BSc Engineering/ Computer Science/ relevant IT qualification
- 3+ years’ experience in a Data domain role (Data engineering) / Data modelling experience in relevant environment
- Data warehouse technical experience – definition /implementation/ integration.
- Strong programming skills in Python and DBA skills (SQL/PSQL/DynamoDB or other).
- Experience with data pipeline and ETL tools and reporting/analytics tools including, but not limited to, any of the following combinations:
- SSIS and SSRS
- ETL Frameworks
- Data conformance
- Caching
- Spark
- AWS data builds.
- Experience with data modelling, data governance, and data quality.
- Expertise in Machine Learning (ML) and deep learning frameworks.
- Proficiency in all aspects of model architecture, data pipeline interaction, and metrics interpretation.
Desired Skills:
- data engineering
- ml
- machine learning
- python
- sql