This role focuses on building scalable data pipelines, integrating diverse data sources, and enabling predictive analytics across cloud environments. This organization operate in the healthcare industry so prior experience in the industry whilst not required, is highly advantageous.
Key Technical Requirements:
- Strong hands-on experience developing data pipelines using Python
- Strong SQL skills, including performance tuning, stored procedures, and data modeling (Star/Snowflake schemas)
- Proven experience with Azure Data Factory (ADF) and Azure Synapse
- Experience with ETL orchestration tools such as Apache Airflow
- Skilled in working with structured and unstructured data, including ingestion from APIs (REST/JSON/XML)
- Familiarity with cloud-based warehousing tools such as Snowflake, Redshift, or BigQuery
- Comfortable working in Azure and/or hybrid cloud environments (Azure/AWS)
- Experience supporting machine learning or predictive modeling pipelines
- Familiar with containerization and version control: Docker, Git, and Azure DevOps
- Understanding of data serialization formats (Parquet, Avro, JSON)
- Knowledge of data validation, quality checks, and observability tools (Azure Monitor, logging frameworks, etc.)
Candidates will be expected, during the interview process, to demonstrate deep hands-on technical experience in data pipeline development, cloud orchestration, and ML-ready data infrastructure.
This position will require the successful applicant to work 5 days per week on site.