Senior Data Analyst

About Gigs

At Gigs, we're building the operating system for mobile services—a platform that lets tech companies embed global connectivity into their products effortlessly.

Just as Stripe lets any business add a payment button in seconds, Gigs empowers platforms to weave in connectivity—bridging the traditional world of telecom with modern tech. From fintechs launching mobile services to HR platforms offering work phone plans, we automate provisioning and remove telecom complexity.

Our team of around 100 people across the US and Europe, backed by nearly $100 million in funding from Ribbit Capital, Google, and Y Combinator. As one of the fastest‑growing tech companies, bringing together early‑stage engineers, product builders, and business athletes from companies like Stripe, Airbnb, and Shopify. We’re tackling deep technical and regulatory challenges to make connectivity truly seamless.

If you’re driven by curiosity, creativity, and the chance to shape the future of telecom, we’d love to hear from you.

As a Senior Data Analyst, you’ll be a foundational part of our data team — shaping how data is modeled, shared, and turned into insight across the company. You’ll join a team of 3 spread across data engineering, analytics engineering and insight generation. This will be the second dedicated Senior Data Analyst in the team.

• 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.

• 8+ 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.

The truth is, what we're building isn't easy. We expect a lot, and operate with urgency and ownership. This won’t be the right place for everyone, and that’s okay.

This role probably isn’t a fit if:

• You need a lot of structure, or layers…