aSenior Data Platform Engineerto

growing above 50% CAGR and with more than 100 Million in Annual Recurring Revenue. Over 5000 businesses, more than 2 million shoppers, and 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 4.5/5, and a Glassdoor rating of 4.3/5. About the role We're looking for aSenior Data Platform Engineerto join our Data Platform team and help us scale se Qura's data ecosystem throughautomation, platform capabilities, and self-service tooling. Your mission will be to help evolve our Data Platform as a Product, enabling software engineers, analysts, data scientists, and business teams to leverage data across its lifecycle - from ingestion to discovery - while ensuring security, governance, and reliability are built into the platform by default. The goal is to empower teams across the company to access trusted data and make better, data-driven decisions. This role goes beyond building pipelines. You'll designthe guardrails, abstractions, and platform capabilitiesthat make it easy for other teams to build and scale their own data products safely and efficiently. You'll work in acloud-native environment on AWS, where Infrastructure as Code, observability, and automation are fundamental engineering principles. What challenges you'll be solving Design and evolve theself-service Data Platform, enabling engineering and business teams to build and manage their own data products autonomouslyIdentify friction points for internal data consumers andbuild platform capabilities that improve developer experienceDesign and maintain a"Golden Path" for data pipelines, enabling teams to deploy new pipelines in minutes instead of weeksEmbeddata governance, observability, lineage, and access controldirectly into platform capabilitiesImprove thereliability, performance, and cost efficiencyof our data infrastructureLead architectural discussions and mentor engineers ondistributed systems and platform designEvangelize the platform internally to drive adoption across teamsAbout the Data team Team mission To build and evolve aself-service data platformthat empowers engineering teams, analysts, and data scientists to build, discover, and scale their own data initiatives withbuilt-in governance, observability, and minimal friction. What we own The full lifecycle of data across the company: extraction, ingestion, landing, transformation, governance, and observabilityThe data infrastructure and platform capabilities that enable teams to create and scale their own data productsCore platform components that ensure data quality, compliance, lineage, and discoverabilityThe evolution of our data platform into a self-service ecosystem where teams can autonomously manage their data lifecycleTeam Structure The Data Platform team is a key part of the Data organization, which also includes the Head of Data, Data Governance Lead, Data Science & AI, and Data Analytics teams. The Data Platform team currently consists of a Data Platform Lead, four Data Engineers, and one MLOps Engineer. They collaborate closely with the Infrastructure Platform team and the rest of the Data organization to build and evolve the company's data platform. How we work Platform mindset: we buildcapabilities and tooling, not one-off solutionsEngineers treat internal teams asplatform customersStrong collaboration withInfrastructure Platform, Data Science & AI, and Data Analytics teamsInfrastructure-as-Code and automation are core engineering principlesWe are transitioning from areactive ticket-based model to a product-oriented platform teamWhat to expect in the next 90 days Month 1:You'll immerse yourself in our data stack and our Data Platform philosophy. You'll meet engineers, analysts, and product teams to understand their current challenges and friction points when working with data. You'll contribute early improvements to our Infrastructure-as-Code, pipelines, or, closely with our values. With us, you will have challenging projects to work on and push your skills and knowledge. In addition, we are very proud of the unique office we have, which offers a comfortable and inspiring environment to work in with everything you need. 23 vacation days + 2 days of free disposal per year.Flexible compensation plan for transportation, restaurants, and kindergarten with Cobee.Health insurance discounts with Sanitas and DKV.Flexible working hours.A personal budget for professional development.Office workshops and meet-ups to encourage community participation and career growth.Hybrid or remote workMoreover, we have aWellness Programthat embraces a holistic approach by covering 6 areas (occupational, physical, financial, emotional, social, environmental consciousness). Each area will include a variety of activities, and you'll be able to choose from 34 different activities that best meet your needs to configure a plan that best works

observability stack, with the goal of identifying and fixing a developer experience pain point. Month 2:You'll start contributing to the long-term platform roadmap. You'll help define standardized ingestion patterns that move us away from bespoke pipelines and toward reusable, scalable platform capabilities. Your goal will be to reduce "Time-to-Data" for one of our key business domains. Month 3:You'll lead a strategic platform initiative from design to deployment, such as evolving our data discovery layer or improving automated change detection. During se Qura Week (when the whole company gathers at our Barcelona HQ), you'll present your work to the engineering organization, showing how the evolution of the data platform directly enables faster and better business decision-making. By this point, you'll have delivered a platform component that allows a non-data team to independently deploy a data producer or consumer. Tech stack & environment️ Our data platform runs onAWSwith Kubernetes (EKS) and everything managed viaTerraformandHelm. CI/CD is handled with Git Hub Actions and Jenkins. We ingest data from multiple sources usingAirbyte, store it in S3 and Redshift, transform it withdbt, and orchestrate pipelines withAirflow. For governance and discovery, we useOpen Metadata, while analytics are delivered throughMetabase. Observability is implemented withPrometheus, Grafana, Thanos, Elastic, and Tempo, and our infrastructure and automation scripts are mainly written inPython, Terraform, and Helm.What we are looking for: Must have: 7+ years of experience inData Engineering, Data Platform Engineering, or Infrastructure EngineeringStrong experience building and maintainingdata platforms or distributed systemsExperience withAWS cloud environmentsSolid experience withKubernetes and containerized infrastructureStrong experience withInfrastructure as Code (Terraform, Helm)Experience implementingobservability, monitoring, logging, and alerting systemsStrong engineering rigor: version control, testing, modular design, and documentationHigh autonomy, ownership, and ability to drive technical decisionsProficiency in English for daily communication, documentation, and technical discussionsExperience working with AI augmentation tools for daily and engineering tasks.Nice to have: Experience implementingdata observability frameworks(Elementary, Great Expectations, etc.)Experience implementingChange Data Capture (CDC)pipelinesExperience withAirflow or other DAG orchestration toolsExperience buildingself-service platforms for data teamsFamiliarity with modern data lake formats such asApache IcebergWhat we offer We have a strong and sustainable foundation, where we provide a secure and reliable workplace. You have the freedom and trust to make the best contribution possible. One of our most valued strengths by our employees is our fellowship and supportive culture, which fosters a sense of belonging by working

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