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Key skills for this role
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.
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.
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More from this employer
Hyderabad, IND
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, IND
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.
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.
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 .
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
Objective: Validate ability to design data pipelines + analytics framework for Vibecoderz.
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).
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).
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.
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.
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.
Implement a Python ETL pipeline that: Listens to Pub/Sub events. Writes processed data into Neo4j + BigQuery. Handles error retries + logging.
Listens to Pub/Sub events.
Writes processed data into Neo4j + BigQuery.
Handles error retries + logging.
Architecture doc (3–4 pages).
Dashboard screenshots or link.
GitHub repo with ETL code + instructions.
Verified company details for this employer are not available yet.
USD 12000-24000 yearly / year
Full-time
Senior · 10+ years experience
Hybrid
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