Data Analyst
Indexed description
The Role
This is a dynamic and evolving role at the heart of our data strategy. You will contribute to our proof-of-concept process, support our data lake project, conduct advanced analytics, and prototype development to support client-facing demonstrations and internal insight generation. The position offers opportunities to work with and learn modern data lake and analytics technologies, whilst collaborating across teams in a fast-growing environment that values innovation and personal development.
Key Responsibilities
- Prototype Development: Carry business requirements through investigation, development, and testing cycles, creating functional prototypes using SQL and modern data tools.
- Data Lake Enablement: Support ingestion, modelling, and transformation of structured and unstructured data into the data lake for scalable reporting and analytics.
- Insight Delivery: Provide high-quality analysis to internal stakeholders (Sales, Solutions Consultancy, Client Success, Product Management) to enhance BAU and strategic initiatives.
- POC Acceleration: Work on proof-of-concept solutions integrated with Power BI and the data lake to improve conversion rates and client engagement.
- Governance & Compliance: Ensure data handling aligns with security, privacy, and regulatory standards, particularly for sensitive and PII data.
- SQL Expertise: Advanced SQL for data manipulation and query optimisation.
- Data Engineering Foundations: Understanding and experience of ETL tools and familiarity with modern data pipelines.
- Cloud & Data Lake Technologies: Exposure to Databricks, AWS/Azure, and data lake architectures desirable.
- Data Visualisation: Proficiency in Power BI or other comparable reporting software for creating dashboards and reports.
- Programming & Automation: Knowledge of Python or similar languages for data wrangling and automation.
- Collaboration Tools: Experience with JIRA and Agile workflows.
- Understanding of Unity Catalog, Delta Lake, or similar governance frameworks.
- Familiarity with MLOps concepts and model lifecycle management.
- Knowledge of Finance and Insurance sectors (beneficial but not essential).
- Analytical mindset with attention to detail.
- Strong communication skills for technical and non-technical audiences.
- Ability to work independently and drive initiatives to completion.
- Flexible and adaptable to evolving business priorities.
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