Principal Data Insight Expert

Responsibilities

• Orchestrate high-stakes customer engagements to align executive objectives with a comprehensive Customer Intelligence Framework, defining critical KPIs, requisite data signals, and high-impact analytical outputs.
• Curate and scale a robust Use-Case Portfolio of reusable intelligence assets, encompassing: Growth Intelligence: Predictive modeling for churn mitigation, engagement optimization, and LTV expansion, Operational Resilience: Proactive anomaly detection, service-level signals, and early-warning systems., Cross-Domain Synthesis: Integrated insights to facilitate holistic, data-driven decision-making.
• Architect technical and functional requirements for enterprise customer programs, establishing rigorous standards for: Data Velocity & Intent: Defining stream/batch requirements and computational logic (segments, triggers, and alerts), Performance Benchmarking: Setting latency expectations and validating success through quantifiable outcome metrics.
• Develop sophisticated Go-To-Market collateral and "Value Storylines" that translate complex technical capabilities into measurable ROI, value hypotheses, and high-conversion POC success criteria.
• Serve as the strategic bridge between Solution Architecture and Engineering to ensure customer propositions are anchored in feasible delivery patterns, specifically regarding low-latency intelligence requirements.
• Synthesize field insights from Tier-1 accounts into actionable requirements for the Data Management product roadmap, driving market-aligned packaging and feature innovation.

Requirements:

• Bachelor’s degree in a relevant discipline (or equivalent professional experience).
• 5+ years of experience in Customer Intelligence / Growth Analytics / Decision Intelligence / Data Strategy roles in data-driven organizations.
• Demonstrated excellence in managing senior stakeholder relationships, with a proven track record of translating complex business imperatives into measurable, high-impact intelligence programs.
• Deep proficiency in designing KPI hierarchies, advanced segmentation models, and growth-lifecycle metrics to facilitate direct "insight-to-action" workflows.
• Sophisticated understanding of low-latency data architectures, including: Solution-Level Architecture: Working knowledge of event-stream ecosystems (e.g., Apache Kafka) to bridge the gap between business requirements and technical feasibility., Operational Intelligence: Expert ability to define high-velocity outputs: such as automated triggers, alerts, and dynamic segments, while maintaining strict standards for reliability and interpretability.
• Hands-on command of SQL, Python, and enterprise BI platforms, leveraging these tools for rapid prototyping, hypothesis validation, and data-driven storytelling.
• Exceptional ability to synthesize complex data landscapes into concise, high-impact narratives and persuasive executive-level presentation materials.

Nice To Have:

• Deep sectoral expertise in Digital Product Marketplaces and Telco ecosystems, with a focus on advanced ARPU optimization, bundle economics, and high-fidelity modeling of customer churn and retention dynamics.
• Strategic proficiency in event-driven design patterns (at a design and review level), including hands-on familiarity with high-concurrency frameworks such as Apache Flink, Kafka Streams, and Spark Structured Streaming.
• Demonstrated experience in implementing rigorous experimentation frameworks, utilizing A/B testing methodologies and uplift modeling to quantify the incremental value of intelligence initiatives.
• Comprehensive understanding of modern cloud-native data environments, with specific emphasis on leveraging Google Cloud Platform (GCP) for scalable data operations.
• Proven track record of architecting Proof of Concept (POC) and Proof of Value (POV) narratives that bridge the gap between initial experimentation and the successful transition into enterprise-scale production programs.