Data Engineer

GoCardless, a Mollie company, is a global leader in bank payments. Over 100,000 businesses, from start-ups to household names, use GoCardless to collect, manage and send bank payments through Direct Debit, real-time payments and open banking. With US$130bn+ processed annually across 30+ countries, we handle recurring and one-off payments without the chasing, stress, or expensive fees. Our end-to-end payment platform also features AI-powered solutions to improve payment success and reduce fraud, alongside connections to over 350 platforms businesses use everyday.

We are headquartered in the UK, with teams and operations spanning North America, Europe and Asia-Pacific.  For more information, please visit www.gocardless.com and follow us on LinkedIn @GoCardless.

Mollie is the leading payments and financial services partner for business, rooted in Europe, with global reach.

You'll sit in our Data and Business Systems group, working with technical and non-technical people across the whole company. You'll be part of a collaborative data engineering team, working closely with analytic engineers, analysts, and business stakeholders to deliver data solutions that scale with our rapidly growing business.

We're a large team with an extensive remit, and we expect every member to work with initiative and be driven — holding each other accountable and to a high standard. Joining our team, you'll work alongside people who strive to be the best they can be, on complex projects across GC's data and business systems stack.

• Strong proficiency in SQL, with experience in relational and/or NoSQL databases.
• Experience designing and maintaining data models (dimensional, normalised, or wide-table approaches) and schema design for analytics or product use cases.
• Hands-on experience building and maintaining ETL/ELT pipelines and ingesting data from third-party or internal sources, using modern data engineering tools (e.g., Apache Airflow, Dataflow, or similar).
• Experience with cloud data platforms, particularly Google Cloud Platform (BigQuery, CloudSQL, Dataflow, Pub/Sub) or equivalent AWS/Azure services.
• Proficiency in Python or another programming language commonly used in data engineering.
• Experience with version control (Git) and CI/CD practices.
• Knowledge of data governance, security best practices, and data privacy regulations.
• Strong communication skills, with the ability to explain technical concepts to non-technical stakeholders.
• Bachelor's degree in Computer Science, Engineering, or related field, or equivalent practical experience.

• Experience in the fintech or payments industry.
• Familiarity with infrastructure as code (Terraform, CloudFormation).
• Experience designing or configuring data orchestration platforms and workflow management systems, beyond day-to-day pipeline scheduling.
• Familiarity with data streaming technologies and real-time data processing.
• Knowledge of machine learning pipelines and supporting ML workflows.
• Experience with data visualization tools and business intelligence platforms.