Azure Data Engineer - Databricks

at  VALD

VALD is the world leader in technology for the allied health industry, providing innovative human-measurement technology to over 5,000 clients in over 100 countries. If you have a favorite team in the NBA, EPL, or NFL, there’s a good chance they use VALD Technologies.
Years on from its humble beginnings in Brisbane, Australia, VALD has grown to a team of over 220 team members in 30 countries, with five offices across four continents.
Driven by a multidisciplinary team of researchers, clinicians, sports scientists, designers, developers and engineers, VALD’s suite of systems offer unparalleled insight into human movement, performance, injury risk and rehabilitation.

ABOUT THE ROLE

VALD is building the world’s largest musculoskeletal database, with over two billion data points and counting. Using this data, we can help practitioners to objectively assess patients’ progress and make more accurate, data-informed treatment decisions. We are looking for an experienced data engineer to help shape the future of the VALD Data Lakehouse.

IN THIS ROLE, YOU WILL:

• Maintain the health of VALD’s data ingestion and transformation pipelines in Azure Databricks.
• Add new data sources, implement business rules, and produce new metrics to provide users with greater insights, supporting key business decisions.
• Work closely with the Product team to develop new data models for VALD’s expanding product suite, following best practices in Kimball dimensional modelling.
• Partner with the Data Science team to build new solutions that extend VALD’s leadership in human movement technology, including normative data serving, secure client data sharing, and MLOps infrastructure.
• Use vendor tools to monitor and improve the data quality and security in the Databricks lakehouse.
• Serve as a data domain expert with an in-depths understanding of our products.

This role is a fantastic opportunity within a fast-growing team. It’s suited to someone with a positive attitude who thrives in a fast-paced, high-pressure environment. The ideal candidate will bring:

• Proven data engineering experience with Azure technologies, including Azure Databricks, Azure SQL Database and Azure Data Lake Storage.
• Proficiency in Spark SQL, PySpark, and T-SQL programming languages.
• Ability to create semantic models, measures, and dashboards in Power BI, including DirectQuery connections.
• Strong written and verbal communication skills.
• Experience developing CI/CD pipelines and following DevOps best practices.