Senior Data Analyst

Responsibilities

• Collaborate cross-functionally with teams like Finance, Growth, Product, and Operations to understand their needs and ensure data is actionable and impactful. This could mean delivering a dashboard, an insight, or a data model powering automation.
• Be a thought partner on how we define core metrics, track business performance, and build trust in data across Gigs.
• Empower internal teams by leveling up power users and educating data consumers, through clear communication, thoughtful documentation, stakeholder collaboration, and occasional training sessions.
• Build the analytics content that matters, both internally and externally. Work with the Product team to identify key customer-facing metrics and play a crucial role in delivering those insights via dashboards and data products.
• Work end-to-end: define new data points with product, translate messy source data into clean, reliable models that power dashboards, metrics, and product decisions.
• Work with a modern event-based data platform across Bigquery, Fivetran, dbt, dagster, Lightdash and Hex.

Requirements

• 6+ years of experience in analytics with a focus on end-to-end delivery.
• Strong understanding of data modeling best practices (e.g. dimensional modeling, testing, documentation).
• Skilled at building alignment and managing expectations with both technical and non-technical stakeholders.
• Experience translating complex business requirements into well-structured data pipelines and models.
• Familiarity with Git, CI/CD, Python and strong SQL.
• A product mindset: care about usability, performance, and building for scale. See the content you deliver as a product.
• Experience working in small/early data teams and larger data platforms.
• Clear communicator who can explain complex topics to non-technical stakeholders.
• Strong bias for action: move quickly, deliver incrementally, ship v1, identify gaps and fill them with stakeholders.

Nice-to-Haves

• Worked closely with Finance stakeholders.
• Product experience in a B2C context (to support customer launches and ongoing implementations).
• Experience with customer-facing data products.
• Experience working in fast-moving startups or remote-first teams.