Senior Data Analytics Engineer
Skills
Azure Data FactoryDevopsApache SparkConsumer TextilesContextData AnalyticsData Warehousing
What the job involves
The main requirements, responsibilities and hiring steps.
Requirements
- Strong experience with Python PySpark Spark SQL and SQL (T-SQL)
- Hands-on experience with Azure Data Factory and Databricks
- Experience designing data warehouse and data mart models including fact dimension design and slowly changing dimensions
- Knowledge of metadata-driven orchestration patterns and platform contract design
- Experience with Power BI or Fabric semantic models and report delivery workflows
- Experience with Azure DevOps pipelines YAML and multi-environment deployment practices
- Strong stakeholder communication skills including requirements gathering and status reporting
- Experience mentoring coaching or leading engineers
Nice to have
- Collaborative
- Analytical
- Proactive
- Detail-oriented
- Influential
- Mentoring mindset
Day to day
- Design and build ingestion pipelines across multiple sources using ADF and Databricks orchestration patterns.
- Develop and optimise data transformations in Databricks, including fact and dimension modelling for data marts.
- Lead a small engineering team while partnering closely with business stakeholders, reporting teams, and data product owners to deliver trusted analytics products.