Analytics Engineer
swap
Híbrido
London
Data
Business Intelligence
Web Master
Job Score
100 pts
Hybrid model (+80)
Data (+10)
Business Intelligence (+10)
Web Master (+10)
About Swap
Swap is the infrastructure behind modern agentic commerce. The only AI-native platform connecting backend operations with a forward-thinking storefront experience.
Built for brands that want to sell anything - anywhere, Swap centralises global operations, powers intelligent workflows, and unlocks margin-protecting decisions with real-time data and capability. Our products span cross-border, tax, returns, demand planning, and our next-generation agentic storefront, giving merchants full transparency and the ability to act with confidence.
At Swap, we’re building a culture that values clarity, creativity, and shared ownership as we redefine how global commerce works.
About the Role
We're looking for a passionate and pragmatic Analytics Engineer to join our Analytics Engineering team, helping to scale our stack for a new data-driven era at Swap.
This is an important contributor role within the team, offering a good degree of ownership and the chance to help build a scalable, modern data architecture. You’ll build and maintain the data models that power our entire business—from internal commercial insights for Sales and Finance to the trusted data sets enabling customer-facing agentic systems.
We need a hands-on builder excited to contribute to our high-quality dbt project, help shape our analytics vision, and support the scaling of our models as we grow. If you thrive in a fast-paced, collaborative team with high ownership and impact, we'd love to hear from you!
Key responsibilities
dbt Development: Scale our dbt project, shaping its architecture and CI/CD processes to support company-wide initiatives.
Data Modelling & Architecture: Contribute to our data modelling strategy, helping to build and maintain the core set of performant, scalable, and trusted data models that power all downstream consumers—from our internal BI tool to our customer-facing agentic systems and analytics APIs.
Data Quality & Governance: Champion and implement robust data quality standards, PII governance, testing, and documentation to ensure our data is trustworthy and reliable as we scale.
Stakeholder Partnership: Partner with commercial (Sales, Finance) and product teams on data needs, assisting in translating business questions into data requirements and helping to manage delivery expectations.
BI & Self-Service Enablement: Contribute to the development and refinement of foundational data assets in our BI tool (Lightdash), helping stakeholders and analysts access insights effectively.
What we would like to see
Solid experience in a data-focused role such as Analytics Engineering, Data Engineering, or BI Development, or equivalent academic experience.
Hands-on experience with dbt (dbt Core/Cloud).
Strong proficiency in SQL and good understanding of data modelling patterns.
Experience with a modern cloud data warehouse (Snowflake, BigQuery etc).
Experience with version control using Git.
Good communication skills with the ability to collaborate effectively with both technical and non-technical stakeholders.
A detail-oriented mindset with a willingness to learn and contribute to building trustworthy data products.
Diversity & Equal Opportunities:
We embrace diversity and equality in a serious way. We are committed to building a team with a variety of backgrounds, skills, and views. The more inclusive we are, the better our work will be. Creating a culture of equality isn't just the right thing to do; it's also the smart thing.
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The Data field has undergone a radical transformation with the rise of Generative AI. Data professionals are fundamental for evidence-based decision-making across all industries.
Key specializations include Data Engineering, Data Science, Business Intelligence, Machine Learning Engineering, and Analytics. Tools like SQL, Python, Spark, dbt, and cloud platforms (AWS, GCP, Azure) are essential.
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