Cloud Data Engineer

TransferGo is a growing fintech scale-up on a mission to champion financial freedom with care. We strive to provide tailored, more affordable financial services that make people's hard-earned money go further. Now in our 14th year, with close to 400 employees in offices across Europe and the UK, we’re crafting a brilliant, relevant product that makes a difference in people's lives and the well-being of their families. We’ve come this far by building a talented, diverse workforce on a fair culture and our strong values. Having this strong team of employees, we can serve those who really need our product to make their lives better. Your team & impact Join us on our journey as a Senior Cloud Data Engineer to play a pivotal role in shaping how money is sent worldwide. The Data team owns TransferGo's data platform end to end — ingestion, transformation, orchestration, the Redshift warehouse, and the standards and tooling (including AI-ready data) that let business domains build trusted, self-service data products. A greenfield data function built from the ground up in a ~300-person fintech going AI-native. Modern AWS stack, dbt Core + Airflow, real ownership of infrastructure you provision yourself, and direct influence on platform standards Here’s what you’ll be doing as Senior Cloud Data Engineer: Build and operate production data pipelines end to end — ingestion, transformation, orchestration, monitoring. Develop and maintain dbt models with tests, documentation Author, schedule and debug Airflow DAGs. Provision and own AWS infrastructure as code (CDK / CloudFormation / Terraform). Support the AI-ready data agent and MCP/Redshift access work. Own data quality, observability and CI/CD (GitHub Actions) for owned pipelines. Take a requirement from a stakeholder and be the person who fixes it when it breaks. You’ll report to our Head of Data. Here’s what we’d love from our new Senior Cloud Data Engineer: We don’t expect you to meet every single requirement listed. What matters most is your motivation, mindset, and ability to learn. If you’re excited about this role and think you could be a great fit, we’d really like to hear from you. 3+ years building and operating production data pipelines. dbt in production: models, tests, documentation, multiple environments. Strong Python for production data engineering. Advanced SQL and analytical data modelling. Hands-on AWS: Redshift, S3, Lambda, IAM, Glue, Kinesis, ECS, ECR. Production experience with an OLAP/MPP warehouse (Redshift preferred). Infrastructure as code — AWS CDK, CloudFormation or Terraform; provisions and owns own infrastructure. Airflow: authoring, scheduling and debugging DAGs end to end. CI/CD with GitHub Actions. End-to-end ownership: from clarifying the requirement with stakeholders, through design, build, deployment and monitoring, to being the person who fixes it when it breaks. High autonomy — decomposes ambiguous problems…