Major responsibilities:

• Design, develop and optimize scalable ETL processes and data pipelines
• Develop and maintain BI solutions, data marts and analytical datasets
• Design and optimize complex SQL scripts, procedures, and data processing workflows
• Manage risks and dependencies by identifying technical and delivery threats such as data quality, legacy alignment and capacity, communicating them to stakeholders, and proposing pragmatic mitigations early
• Align stakeholders by defining and agreeing on approaches and trade‑offs, presenting options and recommendations, and running demos to validate progress and demonstrate value
• Provide technical leadership with hands‑on delivery by reviewing and enforcing architecture, designs, code and SQL/notebooks, and by implementing critical components to ensure consistent quality.

We'd love to hear from you if you have:

• Minimum of 5 years of experience in data engineering, with at least 2–3 years focused on the Azure cloud ecosystem
• Expert in SQL with proven ability to write and optimize complex analytical queries, stored procedures and functions
• Deep knowledge of PySpark and Python for large-scale data processing and building ETL/ELT pipelines
• Understanding data organization principles within a Data Lake (Raw, Silver, Gold layers)
• Experience in administration and development within managed instance environments
• Knowledge of data modeling methodologies (Kimball/Inmon), understanding of Slowly Changing Dimensions (SCD), and history management
• Deep understanding of enterprise Data Warehouse architecture, including the design of dimension and fact tables, and the creation of aggregated data layers
• Financial/Insurance Data Experience, understanding of month-end close processes, data reconciliation, and financial calculation logic
• Experience in performing code reviews, designing pipeline architecture, and overseeing the technical quality of the team's output
• Experience working in Scrum teams, with the ability to decompose high-level business goals into specific technical tasks (User Stories/Tasks) and manage the delivery plan
• English level B2 or higher.
  

Nice to have:

• Experince orchestrating complex task chains in Azure Data Factory
• Knowledge of the insurance domain including premiums, commissions, premium taxes, and actuarial calculations
• Experience with BI tools such as Power BI and understanding how end users consume data from a DWH
• Practical experience performing lift-and-shift migrations of logic from legacy databases to a cloud-based warehouse
• Azure certification preferred, for example Microsoft Certified: Azure Data Engineer Associate (DP-203).