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)