Senior Data Platform Engineer
SeQura
About seQura
SeQura provides innovative, flexible and easy-to-use payments technologies that help merchants acquire, convert and retain more customers. We make a difference in sales performance by tailoring our solutions to different verticals (Retail, Education, Optics, 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 in the scaleup phase. Present in southern Europe and Latin America, we are 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 a Senior Data Platform Engineer to join our Data Platform team and help us scale seQura’s data ecosystem through automation, 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 design the guardrails, abstractions, and platform capabilities that make it easy for other teams to build and scale their own data products safely and efficiently. You’ll work in a cloud-native environment on AWS , where Infrastructure as Code, observability, and automation are fundamental engineering principles.
What challenges you’ll be solving
- Design and evolve the self-service Data Platform , enabling engineering and business teams to build and manage their own data products autonomously
- Identify friction points for internal data consumers and build platform capabilities that improve developer experience
- Design and maintain a “Golden Path” for data pipelines , enabling teams to deploy new pipelines in minutes instead of weeks
- Embed data governance, observability, lineage, and access control directly into platform capabilities
- Improve the reliability, performance, and cost efficiency of our data infrastructuren
- Lead architectural discussions and mentor engineers on distributed systems and platform design
- Evangelize the platform internally to drive adoption across teams
About the Data team
Team mission
To build and evolve a self-service data platform that empowers engineering teams, analysts, and data scientists to build, discover, and scale their own data initiatives with built-in governance, observability, and minimal friction .
What we own
- The full lifecycle of data across the company: extraction, ingestion, landing, transformation, governance, and observability
- The data infrastructure and platform capabilities that enable teams to create and scale their own data products
- Core platform components that ensure data quality, compliance, lineage, and discoverability
- The evolution of our data platform into a self-service ecosystem where teams can autonomously manage their data lifecycle
Team 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 build capabilities and tooling , not one-off solutions
- Engineers treat internal teams as platform customers
- Strong collaboration with Infrastructure Platform, Data Science & AI, and Data Analytics teams
- Infrastructure-as-Code and automation are core engineering principles
- We are transitioning from a reactive ticket-based model to a product-oriented platform team
What 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 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 seQura 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 & environment
Our data platform runs on AWS with Kubernetes (EKS) and everything managed via Terraform and Helm . CI/CD is handled with GitHub Actions and Jenkins. We ingest data from multiple sources using Airbyte , store it in S3 and Redshift, transform it with dbt , and orchestrate pipelines with Airflow . For governance and discovery, we use OpenMetadata , while analytics are delivered through Metabase . Observability is implemented with Prometheus, Grafana, Thanos, Elastic, and Tempo , and our infrastructure and automation scripts are mainly written in Python, Terraform, and Helm .
What we are looking for
Must have:
- 7+ years of experience in Data Engineering, Data Platform Engineering, or Infrastructure Engineering
- Strong experience building and maintaining data platforms or distributed systems
- Experience with AWS cloud environments
- Solid experience with Kubernetes and containerized infrastructure
- Strong experience with Infrastructure as Code (Terraform, Helm)
- Experience implementing observability, monitoring, logging, and alerting systems
- Strong engineering rigor: version control, testing, modular design, and documentation
- High autonomy, ownership, and ability to drive technical decisions
- Proficiency in English for daily communication, documentation, and technical discussions
- Experience working with AI augmentation tools for daily and engineering tasks.
Nice to have:
- Experience implementing data observability frameworks (Elementary, Great Expectations, etc.)
- Experience implementing Change Data Capture (CDC) pipelines
- Experience with Airflow or other DAG orchestration tools
- Experience building self-service platforms for data teams
- Familiarity with modern data lake formats such as Apache Iceberg
What 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 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 work
Moreover, we have a Wellness Program that 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 for you.
Which are the next steps?
- Interview with People Team
- Technical take‑home assessment (async)
- Live Peer review of the assessment
- Meet the team
We kindly ask that you submit your CV in English as it is the official language of our community.
We promote equal opportunity to all, regardless of age, color, gender identity, medical condition, physical or mental disability, race, religion, sexual orientation, or any other characteristic. We have an inclusive environment, and respect is above all.
Do you want to be part of the change? Join us!
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