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Senior Analytics Engineer

SeQura
CompanySeQura
CategoryEngineering
LocationBarcelona
RemoteOn-site (inferred)
EmploymentNot stated
LevelSenior
SalaryNot stated by the employer
Posted
Last verified30 Jul 2026
SourceEmployer career page (recruitee)
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Description
About seQura seQura provides innovative, flexible and easy-to-use payment technologies that help merchants acquire, convert and retain more customers. We make a difference in sales performance by tailoring our solutions to different sectors, to address their unique pain points and deliver superior results in Retail, Education, Eyewear, Repairs and Travel. We also empower smart shopping to consumers who seek more value, convenience, and flexibility in their shopping, with new payment experiences that allow them to save, access interest-free credit, or pay in small, comfortable installments of up to 24 months. Born in Barcelona, seQura is a privately-owned fintech, currently expanding throughout southern Europe and Latin America, growing above 50% CAGR. Over 6000 businesses, almost 3 million shoppers, and almost 400 employees continue to rate us as one of the most loved and trusted fintechs out there, with an NPS of 87%, a Trustpilot rating of 4.7/5, and a Glassdoor rating of 4.1/5. About the role 🤓 We are looking for a Senior Analytics Engineer to own the analytics enablement layer across seQura's core business domains — building the trusted, well-governed data foundation that business, product, and data science teams rely on to make decisions and ship models. This role sits at the intersection of data modeling, business domain understanding, governance, and semantic precision. You will design and deliver production-grade dbt models, shape the semantic layer to be AI-ready, and set the quality bar for the analytics enablement team. You will work closely with business circle leads, Data Scientists, across Risk, Finance, Payments, and Collections, and the Platform and Data Engineering team. What challenges you'll be solving 🚀 Championing a single source of truth for core business metrics — unifying definitions, socializing, and governing the canonical KPIs used across seQura, so that whether a metric appears in a dashboard, a DS model, or an executive report, it means the same thing. Building domain data products that serve both operational reporting and ML feature needs, ensuring downstream teams can self-serve reliably. Designing, building, and shipping production-grade dbt models across multiple business domains — Payments, Debt Collection, Risk, and Finance — writing clean, well-tested, and well-documented SQL. Owning the governance layer: data contracts, column-level lineage, tests, and semantic definitions — not just shipping models, but making them trustworthy. Structuring the semantic layer to be machine-readable and AI-ready, supporting both self-serve BI and AI-powered use cases. Setting and upholding standards for testing, documentation, and data quality across the analytics engineering team. Collaborating closely with Data Scientists, circle leads, and the Platform team to understand domain logic deeply and translate it into precise, unambiguous data models. Making cross-domain architectural decisions with a systems mindset — thinking beyond individual models to how the full data layer fits together. About the Data team 🧩 Team mission To turn seQura's raw data into trusted, well-governed data products that power decision-making across the company. The team builds the foundations that enable Product, Finance, Risk, Payments, Data Science, and AI teams to work with reliable, consistent, and discoverable data, ensuring everyone speaks the same language when making decisions. What we own The dbt transformation layer across business domains The Single Source of Truth (SSOT) for key business metrics Semantic models that enable consistent reporting and analytics Data contracts and governance standards across domains Data lineage, documentation, and discoverability Data quality, testing, and monitoring to ensure trusted data products Team Structure The Analytics Engineering
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