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Deliver data pipelines or products that support our business operations and research, providing clear documentation on specifications and having a deep understanding of each solution at the data, technical and business process levels
Implement data engineering best practices to standardise the development process
Design and maintain data integration frameworks for multiple data sources (e.g. practice management systems, lab systems, registries)
Be responsible for ensuring that high quality data is presented from the products to our researchers, and data dictionaries are maintained in the data catalogue
Requirements:
Educated to degree level in a relevant IT subject
Expertise in designing and implementing data pipelines using Azure services (Azure Data Factory, Data storage), Spark and Databricks
Expertise in data modelling, database design and designing enterprise data architecture
Azure Data Stack
SQL server, NoSQL, Nanobricks, ADT, Spark, Data Tables, API, PostgreSQL
Knowledge of ETL/ELT frameworks and data integration patterns with programming experience with Python or PySpark
Data modelling
Used to working with product teams
Ability to collaborate and communicate with stakeholders and product manager
Nice to have:
Experience of the life sciences sector
Experience working with structured and semi-structured data, preferably having worked previously with a variety of life science data (e.g. omics, health records)