Data Product Analyst

What you will do

We believe in using the best tools to stay effective and efficient. You will be expected to master and evolve our data ecosystem:

Data project ownership & delivery

Managing a data project from start to finish using agile method, helping stakeholders to refine their questions into structured data projects, advising stakeholders on what to measure, how to model it, and which tool to use and facilitating stakeholder discussions to bridge the gap between high-level business goals and technical execution.

Deliver end-to-end solutions, from ingestion and modeling to executive-ready visualizations and summaries.

Technical stack

Modeling & Architecture: Build and maintain scalable models using dbt (SQL) and provide critical reviews of event schemas for our event-based platform.

Modern Workflow: Leverage Cursor and Git to accelerate development and ensure code quality and version control.

The Analytics Hub: Own the user experience across Mixpanel, Tableau, Metabase, and Atlan, ensuring they serve as the single source of truth.

Data literacy

Onboarding and empowering users to self-serve, effectively reducing the data team as a bottleneck.

Handling ad-hoc requests ranging from querying specific datasets to providing technical guidance on our tooling landscape.

Participating in Level 1 technical support, including monitoring dbt jobs and Tableau extracts to ensure the reliability of our products.

Project Governance: Use Jira for roadmap visibility and dbt/Confluence/Atlan for high-quality documentation that survives handoffs.

Continuous Platform Improvement

You act as a bridge to Data Engineering. You’ll proactively surface data debt, documentation gaps, and tooling friction to ensure the platform gets simpler and stronger over time. You’ll also ensure high standards for PII handling and security policies are built into every delivery.

Experience and qualifications

Proven Experience: 3–5+ years in a Data Analyst, Data Product Analyst, or Analytics Engineering role, ideally within a fast-paced environment.

Project Leadership: A track record of taking the lead with stakeholders—successfully translating high-level business ambiguity into structured, actionable data projects. You have experience helping and mentoring other team members.

Technical Mastery: hands-on experience with dbt / SQL (modeling, testing, and documentation).

Hands-on experience with data visualization tools (Tableau, Mixpanel, or similar)

The Modern Workflow: Comfort working in a version-controlled environment (Git) and an interest in leveraging AI-assisted development tools (like Cursor) to drive efficiency.

Data Storytelling: The ability to distill complex findings into executive-ready summaries and visualizations that drive decision-making.

You are fluent in English both written and spoken

Familiarity with data governance practices (PII handling and access control).

Experience in Product Analytics or working directly with Product Managers a nice to have

Familiarity with data engineering concepts (Data Lake, Data Warehouse, ETL / ELT pipeline) and tools (AWS, redshift, Lamdas, Databricks) is a plus