Head of Data Analytics

Role Overview You’ll be the custodian of truth at Vibecoderz . Every decision — from TutorAgent personalization to growth funnels — depends on the data pipelines, analytics frameworks, and event taxonomies you design. This is not about reporting dashboards alone. This is about building a data foundation that fuels personalization, insights, and growth at scale .

You’ll own the Developer Graph, Firestore events, Neo4j pipelines, and Amplitude/Mixpanel dashboards , and ensure everyone — from engineers to CMO — can trust the numbers they see. Your mission is to make data a first-class citizen across Vibecoderz: accessible, accurate, and actionable.

Key Responsibilities

Data Architecture & Pipelines Design and own Vibecoderz’ data stack : Firestore (events), Neo4j (Developer Graph), Redis (cache), BigQuery (analytics warehouse). Build real-time pipelines from TutorAgent sessions to Developer Graph updates. Ensure data quality, lineage, and governance across all systems. Analytics & Event Taxonomy Define Vibecoderz’ event schema (sign-ups, activation, Byte Course completions, artifact usage, retention markers).

Partner with PM/Head of Growth to implement cohort analysis, funnels, and churn prediction . Enforce a consistent taxonomy across product, marketing, and community data. Personalization & Developer Graph Architect and optimize the Developer Graph in Neo4j. Design pipelines for real-time knowledge updates and personalized course recommendations.

Partner with AI/Prompt Engineers to use graph data for context injection and personalization. Growth & Retention Analytics Provide the CMO/Head of Growth with conversion, retention, and LTV dashboards . Run A/B test analysis with statistical rigor. Measure engagement and learning outcomes for every course flow. Team Leadership & Data Culture Build and mentor a data team (data engineers, analysts, ML engineers).

Establish data-driven culture across Vibecoderz: every decision tied to metrics. Champion “single source of truth” dashboards for leadership and investors. Compliance & Privacy Ensure compliance with GDPR, SOC 2, and data privacy regulations . Partner with Security & Compliance head on data encryption and anonymization policies.

Success Metrics 90 Days (Probation): Define Vibecoderz’ event taxonomy and implement tracking for 3 core flows (Text → Course, Voice Tutor, Mini-App). Deliver first growth dashboard (activation, retention, conversion) in Amplitude/Mixpanel. Deploy Developer Graph MVP in Neo4j with sample learner profiles. 12 Months: Developer Graph fully powering hyper-personalization in TutorAgent.

Real-time pipelines handle 100K+ DAUs with <1s latency for graph updates. Growth metrics tracked daily: LTV, churn, cohort retention, funnel drop-offs . Vibecoderz achieves data-driven OKR execution with >80% adoption of analytics dashboards by leadership. Must-Haves 10+ years in data engineering/analytics leadership at product-first companies .

Deep expertise in event-driven architecture, pipelines, and real-time analytics . Proven ability to scale data systems to 100K+ DAUs . Hands-on with Neo4j (Graph DB), Firestore, Redis, BigQuery . Strong background in cohort analysis, churn modeling, LTV/CAC analysis . Nice-to-Haves Experience in EdTech or developer platforms .

Contributions to open-source data tools or analytics frameworks. Prior founding data leader or startup scaling experience. Familiarity with AI-driven personalization and recommendation systems . Tech Stack Visibility Data Sources: Firestore (events), GitHub, TutorAgent logs Graph DB: Neo4j Aura Pipelines: Pub/Sub, Cloud Tasks, Cloud Workflows Storage/Warehouse: BigQuery, Firestore, Redis Analytics: Amplitude, Mixpanel, GA4, custom dashboards Infra: GitHub Actions, Terraform, GCP Compliance: GDPR, SOC 2, ISO 27001 Assessment Objective: Validate ability to design data pipelines + analytics framework for Vibecoderz.

Assessment (3-Part): Data Architecture Design (Written) Draft a data architecture doc for Vibecoderz covering: Event taxonomy for TutorAgent (session start, artifact generated, quiz taken). Pipeline flow from Firestore → Pub/Sub → Neo4j → BigQuery. Data governance policies (lineage, retention, anonymization). Analytics Dashboard (Practical) Build a sample dashboard in Amplitude/Mixpanel/Looker showing: Funnel: Sign-up → Course Start → Artifact Created → Certification.

Retention: 1-day, 7-day, 30-day. Conversion: Free → Pro → Teams. Coding Assessment Implement a Python ETL pipeline that: Listens to Pub/Sub events. Writes processed data into Neo4j + BigQuery. Handles error retries + logging. Deliverables: Architecture doc (3–4 pages). Dashboard screenshots or link. GitHub repo with ETL code + instructions.