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Open nowPosted 98 days ago

Senior Data Analytics Specialist

Workable (global search)108,016 open roles

Where
Egypt
Work mode
Remote
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Your applicationOpen nowSenior Data Analytics SpecialistWorkable (global search) · Egypt

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Early applications get read.

7.9% of postings close within 7 days. Measured by our own scanner across the market. Workable (global search) postings stay open a median of 7 days.

Share of postings closed within
  1. 1.6%1 day
  2. 3.6%3 days
  3. 7.9%7 days
  4. 14.9%14 days
  5. 34.0%30 days
This job: posted 98 days ago

Workable (global search) median: 7 days open

The posting

  • Business insight and decision support: Translate strategic and operational questions into clear analyses, dashboards, reports, and recommendations for leadership and functional teams.
  • KPI and metrics ownership: Define, document, and govern business metrics across fuel consumption, transaction activity, customer adoption, fleet performance, station coverage, invoicing, product usage, savings, churn, and operational efficiency.
  • Dashboard and reporting delivery: Build reliable self-service dashboards for executives, product, sales, finance, operations, customer success, and country or regional teams.
  • Customer and product analytics: Analyze user journeys, feature adoption, customer cohorts, fleet behavior, transaction trends, fuel limits, budget usage, and drop-off points to guide product and growth decisions.
  • Operations and finance analytics: Support reconciliation, invoicing, station performance, wallet movement, service usage, cost analysis, revenue tracking, and profitability insights.
  • Fraud and anomaly insight: Partner with product, operations, and data engineering to identify unusual fuel patterns, tampering indicators, policy exceptions, and monitoring rules that improve trust and control.
  • Experimentation and forecasting: Design analyses for pilots, pricing, campaigns, product launches, and operational changes; support forecasting for consumption, transactions, customer demand, and station utilization.
  • Data storytelling: Present insights clearly, explain trade-offs, quantify impact, and convert analysis into practical recommendations and action plans.
  • Data quality partnership: Work with data engineering to improve source data, metric definitions, documentation, dashboard reliability, and analytics-ready datasets.
  • Analytics mentorship: Set standards for analysis quality, dashboard design, metric governance, and stakeholder communication while mentoring less experienced analysts.

Requirements

Required qualifications

  • 5+ years of experience in data analytics, business intelligence, product analytics, revenue analytics, operations analytics, or a similar analytical role.
  • Advanced SQL skills with the ability to independently extract, transform, join, validate, and analyze complex data from multiple domains.
  • Strong experience building dashboards and data products using Power BI, Tableau, Looker, Metabase, Superset, or similar BI tools.
  • Strong understanding of KPI design, metric definitions, funnel analysis, cohort analysis, segmentation, trend analysis, forecasting, and root-cause analysis.
  • Ability to convert ambiguous business questions into analytical plans, structured hypotheses, and actionable recommendations.
  • Experience working with transactional, product, customer, payment, operational, or financial datasets at scale.
  • Working knowledge of Python or R for analysis, automation, statistical exploration, or notebook-based research.
  • Excellent stakeholder management and communication skills, including the ability to explain technical findings to non-technical audiences.
  • Strong attention to data accuracy, definitions, documentation, and reproducibility.
  • Comfort working in fast-paced product and engineering environments with changing priorities and high ownership expectations.

Preferred qualifications

  • Experience in fintech, fleet management, logistics, mobility, fuel, marketplace, SaaS, or high-volume transaction businesses.
  • Experience with dbt, semantic layers, data catalogs, metric stores, or analytics engineering workflows.
  • Familiarity with fraud analytics, anomaly detection, operational controls, pricing analysis, or customer savings measurement.
  • Experience with A/B testing, causal inference, retention analysis, churn prediction, LTV modeling, or commercial performance analytics.
  • Arabic and English business communication skills are a plus for regional stakeholder engagement.

Core analytics stack expectations

The exact stack may evolve, but the successful candidate should be comfortable operating across the following categories:

  • Analysis: SQL, spreadsheets, Python or R, notebooks, statistical methods, and business case modeling.
  • BI and visualization: Power BI, Tableau, Looker, Metabase, Superset, or equivalent dashboarding tools.
  • Data modeling: dimensional thinking, metric definitions, cohort tables, funnel tables, and curated analytical datasets.
  • Collaboration: requirements gathering, stakeholder workshops, documentation, presentations, and decision memos.
  • Governance: metric catalog, dashboard ownership, access control awareness, and data quality issue management.
  • Product analytics: event data, customer journeys, feature usage, adoption metrics, retention, and conversion analysis.

Benefits

  • Competitive salary and benefits package.
  • Opportunity to work on cutting-edge technology with a passionate team.
  • Career growth and development opportunities.
  • A collaborative and inclusive work environment.
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