A proactive Data & Analytics Engineer to join our lean data team. In this mid-level role, you’ll build and optimise Power BI reports and semantic models, design end-to-end ETL pipelines, and automate data workflows. Ideal candidates have solid data engineering experience and strong data-analysis skills and are eager to tackle everything from database management to API development.
Job Description
Key Responsibilities
Reporting & Analytics
Develop, maintain and optimise Power BIs, SSRS, and paginated Fabric reports.
Translate business requirements into SQL stored procedures, views and tables.
Provide data requested from business units such as Marketing, Sales, Client Services, Finance, Risk & Compliance, and Actuarial.
Data Integration & Automation
Design and implement robust ETL/ELT pipelines using Azure Data Services (Data Factory, Synapse, Data Lake).
Develop REST APIs and leverage Functions, Logic Apps or Spark notebooks to automate workflows and integrate AI.
Database Management
Maintain Microsoft SQL Server and Microsoft Fabric Data Warehouse.
Manage SSIS/ADF packages and embedded business logic within reports.
Assist the Senior Data Engineer with translate business requirements into logical, relational, and semantic data models, aligning database structures with reporting and analytics needs.
Team Support & Mentorship
Learn from and assist the Senior Data Engineer in the development of data architecture, security configuration and data modelling.
Mentor data analysts on tools, processes and coding standards.
Share team responsibilities of reviewing work, hosting huddles, and ticket creation.
Documentation & Governance
Produce and maintain clear documentation for pipelines, procedures and models.
Assist with the maintenance of development of governance technology.
Desired Skills and Experience
Capabilities
3 – 5 years SQL experience, in particular translating complex logic into stored procedures.
Good understanding of ETL design patterns and Azure Data Factory/Synapse analytics.
Proven experience building and optimising Power BI reports and semantic models.
Experience maintaining SQL Server and cloud databases (SSIS, ADF pipelines).
Strong experience with Python and object orientated programming.
Good communication skills for liaising with technical and non-technical stakeholders.
Bonus: exposure to Microsoft Fabric/Databricks, Data Governance, and Azure DevOps CI/CD.
Bonus: Familiarity with REST API development and Azure Functions/Logic Apps.
Experience & Qualifications
Bachelor’s or master’s degree in Computer Science, Data Science, IT or related field.
2–5 years in data engineering or analytics roles, preferably within financial services or technology.
Demonstrated ability to work in a fast-paced, collaborative environment with a “can-do” attitude.
Bonus: Relevant certifications (e.g. Microsoft Certified: Power BI, Azure Data Engineer).
