Data Business Analyst

Mindera; London; On-site; GBP 50,000 - 70,000; Full time

Job summary

A leading company is seeking a Data Business Analyst to bridge the gap between business stakeholders and data teams. This role involves translating business needs into actionable insights, driving process improvements, and delivering data-driven reporting solutions. The successful candidate will collaborate with various departments and utilize BI tools to create impactful dashboards and reports.

Benefits

Competitive day rate

Qualifications

• Experience in gathering and validating business and data requirements.
• Ability to analyze large datasets and identify trends.
• Experience in creating dashboards and reports.

Responsibilities

• Document and validate business and data requirements.
• Collaborate with data teams to design data solutions.
• Support data quality initiatives and resolve discrepancies.

Skills

Analytical Skills

Business Savvy

Data Interpretation

Collaboration

Communication

Tools

Power BI

Tableau

Looker

Job description

We are looking for a highly analytical and business-savvy Data Business Analyst (Data BA). In this role, you will bridge the gap between business stakeholders and data teams by translating business needs into data-driven insights, requirements, and reporting solutions. You will play a key role in shaping our data strategy, driving process improvements, and delivering actionable intelligence to support strategic decision-making.

Requirements

Key Responsibilities

1. Gather, document, and validate business and data requirements from stakeholders across various departments.
2. Analyze and interpret large datasets to identify trends, patterns, and insights that drive business decisions.
3. Collaborate with data engineers, analysts, and developers to design and implement data solutions.
4. Create dashboards and reports using BI tools (e.g., Power BI, Tableau, Looker).
5. Develop and maintain detailed documentation, including data dictionaries, business rules, and process flows.
6. Support data quality initiatives by identifying and resolving data discrepancies or inconsistencies.
7. Translate complex technical data concepts into easy-to-understand insights for non-technical audiences.
8. Assist in testing and validating data pipelines, reports, and dashboards before deployment.

Benefits

Competitive day rate.