Data Analyst - SQL/QlikSense

Daily rate: £365 per inside of IR35

Duration: 12 Months

Location: Hybrid/3 days per week in Chertsey, Surrey

KEY ACCOUNTABILITIES

• Interrogate the data warehouse using SQL (basic level knowledge)
• Using QlikSense for analysis
• Stakeholder engagement, interface between end business users and technical teams
• Be proactive
• Performing customer segmentation and profiling
• Taking large datasets and generate key insights using existing analytics resources, and packaging them for end users in easily digestible formats, and be able to evidence end-user adoption and beneficial outcomes of such insights.
• Reporting and insights pipeline management: Managing a reporting/insights pipeline
• Gathering requirements from the business and managing stakeholder expectations
• Converting end user requests into meaningful and efficient requirements for technical roles eg (Data) Engineers/dev
• Data Brief validation and QA: Checking dev outputs and co-ordinating UAT
• Ongoing validation and QA: Perform ongoing QA of published data outputs to uncover issues related to quality, consistency, and business questions.

SKILLS AND EXPERIENCE:

Essential

• SQL (Basic level knowledge)
• Experience with BI Tools such as Tableau, Power BI, QlikSense, Adobe Analytics etc.
• Advanced Segmentation, data layer understanding, web data collection understanding, D2C experience or equivalent understanding
• Experience of stakeholder engagement,
• Experience as interface between end business users and technical teams
• Experience managing output pipeline.
• Will have had experience of being able to prioritise and triage advanced requests from multiple business-side stakeholders, experience of stakeholder requirements gathering and ability to converting end user requests into meaningful and efficient requirements for technical roles eg (Data) Engineers/dev
• Be able to check dev outputs/co-ordinate UAT (specifically must have enough data knowledge to be able to run reconciliations vs master data sources and new outputs and be able to sniff out non-credible outcomes and own the escalation & resolution of such issues. Be an initial layer of QA screening before getting the business involved.

Desired

• Recommend projects that will enhance our insight capability, turn those recommendations into tangible technical requirements. It's critical that they have the nous to run a sniff test on whether a data output is credible or not (rather than just objectively whether it is doing what it is expected to do on a requirement level.)