> Markdown version of [/jobs/ext/3245631-data-analyst](https://www.wearedevelopers.com/jobs/ext/3245631-data-analyst). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Data Analyst - **Company:** Gigs, Inc. - **Location:** New York, United States - **Experience:** Expert - **Salary:** $165,000.0 - $190,000.0 - **Contract:** Permanent contract - **Skills:** BigQuery, Continuous Integration, Information Engineering, Dimensional Modeling, Python (Programming Language), Git, Data Management, Data Pipelines - **Published:** September 4, 2026 - **Apply:** https://startup.jobs/senior-data-analyst-gigs-8778276 ## About the Role * 6+ years of experience in analytics with a focus on end to end delivery. Having worked closely with Finance stakeholders, Product in a B2C context (to support customer launches and ongoing implementations) or experience with customer-facing data products are strong plus points. * A 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: you care about usability, performance, and building for scale. You see the content you deliver as a product and are interested in having those being used. * This is not your first rodeo. You have worked in small and early data teams, grown along side them and worked in larger teams and data platforms. You've seen what works and doesn't in both and are looking to apply this in your next role. * Clear communicator - you can work cross-functionally and explain complex topics to non-technical stakeholders * Strong bias for action: You move quickly, deliver incrementally, and aren't afraid to ship v1. You identify what's missing and work with stakeholders to fill the gaps. * Experience working in fast-moving startups or remote-first teams is a plus. ## Description As a Senior Data Analyst, you'll be a foundational part of our data team - shaping how data is modelled, shared, and turned into insight across the company. You'll join a team of 3 spread across data engineering, analytics engineering and insight generation. You will be the second dedicated Data Analyst in the team. Salary Range: USD 165,000 - USD 190,000 (The final offer depends on your background, skills, and how you perform through the process. We're open to considering outlier candidates, which may result in an adjustment to the scope and compensation) What You Will Do * 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. You'll 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. * Not every data point is available yet. We all work end to end. Work with product to define new data points, translate messy source data into clean, reliable models that power dashboards, metrics, and product decisions. * You will work with a modern event-based data platform across Bigquery, Fivetran, dbt, dagster, Lightdash and Hex. ## Related Videos - [Data Science in Retail](https://www.wearedevelopers.com/videos/586-data-science-in-retail) - [From Messy Queries to Scalable Systems - How Data Engineering actually works](https://www.wearedevelopers.com/videos/100203-from-messy-queries-to-scalable-systems-how-data-engineering-actually-works) - [How a Small Team Shrank a Microsoft Monorepo by 94%](https://www.wearedevelopers.com/videos/1236-how-a-small-team-shrank-a-microsoft-monorepo-by-94) - [Why and when should we consider Stream Processing frameworks in our solutions](https://www.wearedevelopers.com/videos/1085-why-and-when-should-we-consider-stream-processing-frameworks-in-our-solutions) - [Making Data Warehouses fast. 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