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Tech Stack
Tools & technologiesAzureCloudETLPythonSQLTableau
About the role
Key responsibilities & impact- Collect, clean, validate and manage data from multiple systems and sources.
- Perform data analysis to identify patterns, trends, and correlations.
- Develop and maintain dashboards, visualisations, and reports using BI/analytics tools.
- Work closely with business and technical stakeholders to understand requirements and translate them into data solutions.
- Ensure data integrity, compliance, and alignment with governance and security standards.
- Produce clear, visually compelling insights for non-technical audiences and decision-makers.
- Support data structuring and organisation across systems and connected platforms.
Requirements
What you’ll need- Strong analytical capability with proven experience interpreting complex datasets.
- Excellent written and verbal communication skills, capable of translating data into clear insights.
- High attention to detail with strong data quality and validation discipline.
- Experience with reporting and BI tools (e.g., Power BI, Tableau, Qlik, Excel BI).
- Experience using Python or R for statistical analysis or automation (desirable).
- Knowledge of statistical modelling, forecasting, or predictive analytics (desirable).
- Experience with Azure data services, SQL or cloud-based data stacks (desirable).
- Understanding of ETL processes, data warehousing and large-volume data handling (desirable).
Benefits
Comp & perks- Health insurance
- Pension scheme
- Flexible working hours
- Professional development opportunities
ATS Keywords
✓ Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills & Tools
data analysisdata validationstatistical analysisstatistical modellingforecastingpredictive analyticsETL processesdata warehousingdata handlingdata structuring
Soft Skills
analytical capabilityattention to detailwritten communicationverbal communicationdata interpretationinsight translationstakeholder collaborationdata quality discipline
