Data Intelligence Analyst

Responsibilities 

• Empower VP-level decision-making by delivering rapid, structured analytical intelligence across cross-functional domains, including Business Operations, Product Strategy, and Corporate Functions. 
• Transform fragmented, multi-source inputs; encompassing internal systems, telemetry logs, and external benchmarks, into high-fidelity, analysis-ready datasets. 
• Execute rigorous data normalization, reconciliation, and deduplication to engineer reusable "Analysis Views" anchored to standardized enterprise KPI definitions. 
• Author high-impact intelligence outputs designed for executive consumption, including: 

1. Executive Dashboards: Real-time visibility into mission-critical performance drivers. 
2. Strategic Briefs: Concise narratives identifying variance drivers, downstream implications, and prioritized tactical recommendations. 

• Provide rapid-response analytical support for cornerstone leadership objectives, including: 

1. Monitoring customer lifecycle velocity and product penetration signals. 
2. Analyzing incident patterns, capacity distribution, and early-warning trend detection. 
3. Quantifying productivity benchmarks and strategic program performance. 

• Institutionalize analytical speed by maintaining a library of standardized executive templates, KPI taxonomies, and governed dataset structures for recurring strategic inquiries. 
• Collaborate with General Management across Engineering, Product, and Architecture to harmonize data interpretations, validate assumptions, and ensure a "single source of truth." 
• Uphold the highest standards of discretion and data integrity while managing sensitive, high-stakes corporate information. 

Requirements: 

• Bachelor’s degree in Computer Science / Information Systems / Statistics / Engineering (or equivalent experience). 
• 2+ years of experience in analytics / BI / data analysis roles, with strong execution discipline and stakeholder maturity. 
• Strong analytical foundations: KPI reasoning, trend analysis, segmentation logic, cohorts/funnels (where applicable), and ability to interpret results for business decisions. 
• Strong data preparation capability by comfortable handling messy data, joining across sources, and ensuring consistency before analysis. 
• Strong SQL capability and comfortable with at least one analytics tooling approach (BI platform and/or Python for analysis automation). 
• Ability to work in fast-moving environments: shifting priorities, short deadlines, and iterative problem statements. 
• Strong communication by can deliver concise, decision-grade summaries, not only charts. 

Nice To Have: 

• Extensive exposure to multi-domain intelligence, providing strategic insights across Operations, Delivery, Customer Growth, Human Capital/People Analytics, and Efficiency. 
• Proven ability to institutionalize efficiency by automating complex analytical workflows, utilizing scripting and low-latency pipeline orchestration to ensure seamless, scheduled intelligence refreshes. 
• Solid foundation in cloud-integrated data environments, with a specific focus on leveraging Google Cloud Platform (GCP) to support enterprise-scale data initiatives. 
• Sophisticated understanding of event-driven data patterns and near-real-time monitoring, essential for architecting early-warning systems and proactive operational indicators. 
• Expert-level experience in curating high-stakes reporting suites, including Monthly Business Reviews (MBR), OKR performance tracking, and high-impact excerpts for Board of Directors presentations