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