At a Glance
- Tasks: Transform complex data into clear insights to boost our go-to-market performance.
- Company: Join sunday, a fast-growing tech company revolutionising restaurant payments.
- Benefits: Competitive salary, stock options, remote work flexibility, and comprehensive health insurance.
- Other info: Opportunity to shape your career while working with global teams.
- Why this job: Be at the forefront of data analytics in a dynamic, innovative environment.
- Qualifications: 2-4 years in analytics, strong SQL skills, and experience with cloud data warehouses.
The predicted salary is between 63000 - 77000 £ per year.
About Us
sunday is building the fastest, simplest way to pay in restaurants. With a quick scan of a QR code, diners can pay, tip, and leave in about 10 seconds. We believe great products should feel obvious, not complicated, and we focus relentlessly on keeping things simple while earning trust from restaurants and guests at every interaction. Today, sunday powers payments in thousands of restaurants across the US, UK, and France, helping operators turn tables faster, increase tips, and unlock valuable insights. We push ourselves to go beyond what’s expected, building with ownership, moving fast, and scaling with ambition as we tackle our biggest growth opportunity in the US.
About the Role
As a GTM Data Analyst at sunday, your ultimate goal will be to make our go-to-market performance easier to understand, measure, and improve. You will become an expert in sunday’s data architecture and reporting infrastructure, helping teams across the US, UK, and France turn complex business questions into clear, actionable insight. You can be based in London or in Atlanta. You will report to the Global GTM Program Manager and join a five-person GTM Operations team. This is a highly technical, hands‑on role: you will work closely with GTM operators, RevOps, and Data to build the reporting foundations that help sunday grow intelligently, while also identifying where AI and agentic workflows can make our revenue teams more effective. In your first 6–12 months, you will become an expert in sunday’s data architecture and reporting infrastructure, identify clear gaps in our data and reporting, and deliver solutions to many of them. Join early, grow fast, and shape the journey!
Key Responsibilities
- Serve as the primary analytics resource for GTM operators across the US, UK, and France, delivering complex analyses and ad hoc deep dives.
- Build and own the reporting standard used in sales leadership’s regular GTM performance reviews.
- Build the foundational KPI reporting layer across the funnel, from leadership dashboards to rep‑level execution tools.
- Design and maintain dashboards covering account and territory views, opportunity management, activity, and pipeline analysis.
- Query and model data directly in SQL and BigQuery to answer questions beyond out-of-the‑box Salesforce reporting.
- Maintain data integrity and reporting consistency across regions, systems, and tools.
- Identify opportunities to deploy AI and agentic workflows across revenue processes, and help build the technical foundations they require.
- Support AI‑assisted reporting and analysis workflows, and help drive fluency and adoption of the team’s AI tooling.
About You
Must-haves:
- You have 2–4 years of experience in a data analyst or similar analytics role.
- You have strong SQL skills and can write, troubleshoot, and improve queries independently. This is the most important technical requirement for the role.
- You have experience with a cloud data warehouse; we use Google BigQuery, and experience with Snowflake, Redshift, or an equivalent is also relevant.
- You are fluent in Salesforce objects, reports, and dashboards.
- You have built dashboards and reports in a BI tool; we use Metabase.
- You are comfortable using AI tools to accelerate or improve analytical workflows.
- You pay close attention to data quality and look for the “so what”, not just the output.
- You can understand business needs and translate them into focused analyses and practical reporting solutions.
- You are comfortable working hands‑on with RevOps and Data teams as a technical partner.
Nice to have:
- Exposure to go‑to‑market, sales, or revenue operations environments.
- Experience working with global or multi‑region teams.
- Prior exposure to building or using AI or agentic workflows in a business context.
What we Offer
- £70,000–£85,000 base salary London OR $90,000-$115,000 USD base salary in Atlanta
- Stock Options
- A great office with a balance of in-person and remote work
- Free Vacation Policy
- 100% Employer-Covered Health Insurance
Steps in our Recruitment Process
Thank you for taking the time to apply, and looking forward to getting to know you! sunday is an equal opportunity employer and does not discriminate and all qualified applicants will receive consideration for employment without regard to race, creed, color, sex, affectional or sexual orientation, gender identity or expression, gender, ethnicity, religion, national origin, ancestry, nationality, age, disability, marital status, veteran status, genetic information, or on any other basis prohibited by law (except where an attribute is a bona fide occupational qualification).
GTM Data Analyst employer: sunday
At Sunday, we pride ourselves on being an exceptional employer, offering a vibrant work culture that fosters collaboration and innovation in the heart of Westminster. Our commitment to employee growth is evident through tailored training programmes and opportunities for advancement, ensuring that you can thrive in your role as a Customer Onboarding Specialist. Join us to be part of a forward-thinking fintech SaaS company where your contributions directly impact client success and satisfaction.
StudySmarter Expert Advice🤫
We think this is how you could land GTM Data Analyst
✨Get Involved in Data Science Meetups
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Join professional bodies related to data science, like the Data Science Society or similar organisations. Getting involved can lead to mentorship opportunities and insider knowledge about full-time positions at companies like sunday.
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When you find a suitable opening like GTM Data Analyst at sunday, make sure to apply directly through our website. It gives you an edge and shows you're keen to join our team. Plus, who doesn’t love a direct application? It’s easier than navigating through job boards!
We think you need these skills to ace GTM Data Analyst
Some tips for your application 🫡
Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
Quantify Your Achievements:Employers love numbers! When drafting your CV, highlight your achievements with quantifiable results. For instance, mention how your data analysis led to a certain percentage increase in efficiency or revenue at a previous job or project. These details can really make your application pop!
Craft a Tailored Cover Letter:For a full-time role at sunday, your cover letter should reflect your passion for data science and your excitement about the specific projects or values of the company. Dive into why you’re a good fit, how your skills align with their needs, and any unique perspectives you can bring to the team.
Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at sunday. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!
How to prepare for a job interview at sunday
✨Brush Up on Your Statistics
For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!
✨Showcase Your Projects
Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!
✨Get Comfortable with Python and R
Most data science positions require us to be proficient in programming languages like Python and R. We should practice common libraries like pandas, NumPy, and scikit-learn, and be ready for live coding exercises or algorithm questions. Showing off our coding chops can really impress the interviewers at sunday!
✨Prepare for Case Studies
Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.