WKO MIS & Strategy - Client Data Associate

Job Responsibilities Strengthen data quality —monitor data completeness/accuracy with attention to details, perform root-cause analysis, and drive process improvements to meet applicable requirements and reduce rework. Own periodic and ad hoc reporting to support global Client Onboarding—define requirements with stakeholders, source data (Python/SQL/Databricks), validate results, and deliver executive-ready insights (trends, drivers, “so what,” and recommended actions). Design, build, and enhance dashboards that enable data-driven decisions—partner with business users to translate needs into KPI definitions, data models, and Tableau/Qlik visualizations; ensure usability, consistency, and adoption. Lead process automation opportunities —identify manual/recurring activities and control checks, propose scalable solutions, and implement automation using Python/SQL/Databricks (with documentation, testing, and controls) Manage stakeholder communication and prioritization —triage inbound requests, set expectations on scope/timing, tailor outputs to the right audience (technical vs. non-technical), and anticipate upcoming data needs based on priorities. Required qualifications University degree (Engineering, Computer Science, Actuarial Science, Economy, Business Administration or equivalent). Fluent in English is mandatory, both written and verbally. Other languages are a plus. Advanced knowledge of programming languages is required (Python, SQL, Databricks). Frontend\Data Visualization Skills, proved experience with Tableau, Qlik. 2+ of experience with data management. Preferred capabilities, and skills Technical skills (required): Python, SQL, Excel — able to extract, clean, transform, and analyze data efficiently across these tools Strong logical and analytical problem-solving — structured thinking, hypothesis-driven analysis, and ability to translate ambiguity into clear steps Large-scale data handling — comfortable working with high-volume / complex datasets while ensuring data quality and consistency Data visualization & storytelling — builds clear visuals and explains insights in a way that drives decisions Stakeholder-focused ad hoc analysis — quickly understands stakeholder needs, clarifies requirements, and delivers timely analysis with the right level of rigor Communication skills — clear written and verbal communication; able to explain findings to technical and non-technical audiences Product-aligned mindset — connects analysis to outcomes; prioritizes work that improves user/client experience and business impact Learning agility — ramps up quickly on new domains, tools, and processes; adapts to changing priorities Prioritization & capacity management — prioritizes issues, analysis requests, and workstreams based on impact, urgency, and team bandwidth Collaborative working style — partners effectively with team members and cross-functional groups; shares context and raises risks early Implications / “so what” orientation — identifies implications, risks, and recommended actions from analysis (not just metrics) Executive-ready outputs — contributes to concise communication materials for senior management (summaries, briefs, key messages) Nice to have: JavaScript (basic) and React (basic) — able to support lightweight UI/data visualization needs Databricks — experience building or running analytics workflows in Databricks (e.g., notebooks, pipelines, collaboration)