Data Engineering Lead

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 and approaching 100 Million in Annual Recurring Revenue.
Over 5000 businesses, almost 2 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 4.7/5.

We’re looking for a hands-on and strategic Data Engineering Lead to drive our data engineering efforts and guide a growing team of engineers. You’ll be responsible for designing scalable data architectures, optimizing data pipelines, and ensuring data reliability across the company. Depending on your seniority and profile, you could also take ownership of data analyst workflows and team management.

• Lead, mentor, and grow the data engineering team, setting best practices in architecture, development, and operations.

• Design and implement scalable, reliable, and secure data pipelines and data lake architectures.

• Collaborate with data analysts, data scientists, and business stakeholders to understand data needs and deliver robust solutions.

• Own the development and maintenance of ETL/ELT processes, data quality, versioning, and governance.

• Optimize performance across data workflows, ensuring efficiency and minimal downtime.

• Champion a data-first culture, ensuring our data infrastructure scales with the company’s needs.

• Support the potential integration of data analyst workflows and oversight, depending on your scope and experience.

• Proven experience leading or mentoring data engineering teams.

• Strong communication skills and the ability to work cross-functionally with technical and non-technical stakeholders

• Strong background in designing and implementing data platforms in cloud environments (ideally AWS, but GCP or Azure is also valuable).

• Solid experience with Kafka, Airflow, DBT and modern data warehouses (ideally Redshift, but BigQuery or Snowflake is also valuable).

• Advanced knowledge of Python and SQL.

• Familiarity with Devops culture, CI/CD practices and infrastructure as code (e.g. Terraform).

• Deep understanding of data governance, versioning, and quality control.

• (Nice to have) Experience working with data analysts or BI teams, and ability to guide analytics efforts.

1. Interview with People Team

2. Technical take-home assessment

3. Live Peer review of the assessment

4. Interview with the Director of Engineering

5. Meet the team

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.