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For Companies At a Glance
- Tasks: Transform complex data into reliable datasets that drive business decisions.
- Company: Join a fast-growing B2B SaaS company revolutionising e-commerce with AI.
- Benefits: Competitive salary, flexible work options, and opportunities for professional growth.
- Why this job: Make a real impact by empowering businesses with data-driven insights.
- Qualifications: 4+ years in analytics, strong SQL skills, and experience with dbt projects.
- Other info: Dynamic team environment with a focus on innovation and collaboration.
The predicted salary is between 36000 - 60000 ÂŁ per year.
At Swap Commerce, we are building the agentic commerce infrastructure for the future, enabling businesses to sell anything, anywhere, from a single, unified platform. As a rapidly growing B2B SaaS company, we empower our merchants with AI-driven solutions that boost revenue and increase savings. Data is at the core of our mission, and we are looking for an experienced Analytics Engineer to own our data transformation and modelling layer.
As our Analytics Engineer, you will be pivotal in shaping our data landscape. You will transform complex e-commerce, logistics, and sales data into pristine, reliable datasets that power our product and our business. Your work will directly empower teams across Swap Commerce to move from reactive to proactive, making smarter, data‑driven decisions with confidence and helping our merchants thrive in a global marketplace.
Responsibilities
- Design, build, and maintain robust and scalable data models using dbt (dbt Core/Cloud).
- Transform raw data from various sources into clean, reliable, and analysis‑ready datasets.
- Write advanced, performant SQL to model complex business logic related to global sales, shipping, returns, tax and compliance.
- Implement and champion data quality testing, documentation, and data governance best practices within our dbt project.
- Collaborate with data analysts and business stakeholders to understand their data needs and translate business logic into technical requirements.
- Apply software engineering best practices to the analytics codebase, including version control (Git), code reviews, and CI/CD.
- Optimise our data warehouse for performance and cost‑efficiency.
What We’re Looking For
- 4+ years of experience in a data‑focused role such as Analytics Engineering, Data Engineering, or BI Development.
- Extensive, hands‑on experience building, deploying, and maintaining production‑grade dbt projects.
- You should be highly proficient with dbt's core principles.
- Expert‑level proficiency in SQL and a deep understanding of data modelling concepts (e.g., Kimball).
- Strong experience working with a modern cloud data warehouse (Snowflake, BigQuery, Redshift, etc.).
- Proficiency with version control using Git and an understanding of CI/CD workflows.
- Excellent communication skills with the ability to collaborate effectively with both technical and non‑technical stakeholders.
- A proactive and detail‑oriented mindset with a passion for building trustworthy and high‑quality data products.
Bonus points for:
- Experience in a high‑growth SaaS, e‑commerce, or logistics‑focused company.
- Familiarity with data ingestion tools (e.g., Fivetran, Stitch).
- Experience with Python for data scripting.
Senior Analytics Engineer in City of London employer: Swap
Contact Detail:
Swap Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior Analytics Engineer in City of London
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, attend meetups, and connect with people on LinkedIn. You never know who might have the inside scoop on job openings or can refer you directly.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your data models and projects. This is your chance to demonstrate your expertise in dbt and SQL, making it easier for potential employers to see what you can bring to the table.
✨Tip Number 3
Prepare for interviews by brushing up on common analytics engineering questions. Practice explaining your thought process when tackling data challenges, and be ready to discuss how you've implemented data quality testing and governance in past roles.
✨Tip Number 4
Apply through our website! We love seeing candidates who are genuinely interested in joining us at Swap Commerce. Tailor your application to highlight your experience with cloud data warehouses and your passion for data-driven decision-making.
We think you need these skills to ace Senior Analytics Engineer in City of London
Some tips for your application 🫡
Tailor Your CV: Make sure your CV speaks directly to the role of Senior Analytics Engineer. Highlight your experience with dbt, SQL, and any relevant projects that showcase your data transformation skills. We want to see how you can fit into our mission at Swap Commerce!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to tell us why you're passionate about data and how your background aligns with our goals. Share specific examples of how you've made an impact in previous roles, especially in a B2B SaaS environment.
Showcase Your Technical Skills: Don’t hold back on your technical prowess! Be sure to mention your experience with cloud data warehouses and version control systems like Git. We love seeing candidates who are not just skilled but also proactive in applying best practices in their work.
Apply Through Our Website: We encourage you to apply through our website for the best chance of getting noticed. It’s the easiest way for us to keep track of your application and ensure it reaches the right people. Plus, it shows you’re serious about joining our team!
How to prepare for a job interview at Swap
✨Know Your Data Inside Out
As a Senior Analytics Engineer, you'll be dealing with complex datasets. Make sure you brush up on your SQL skills and understand the data modelling concepts like Kimball. Be ready to discuss how you've transformed raw data into reliable datasets in your previous roles.
✨Showcase Your dbt Expertise
Since dbt is a key part of the role, prepare to talk about your hands-on experience with dbt projects. Bring examples of how you've built and maintained production-grade dbt models, and be ready to explain the core principles of dbt that guide your work.
✨Communicate Like a Pro
You'll need to collaborate with both technical and non-technical stakeholders, so practice explaining complex data concepts in simple terms. Think of examples where you've successfully communicated data needs or insights to different teams.
✨Be Ready for Problem-Solving Questions
Expect questions that test your analytical thinking and problem-solving skills. Prepare to discuss specific challenges you've faced in data transformation or modelling, and how you approached them. This will show your proactive mindset and detail-oriented approach.