Join the data products team at a fintech company building commercial banking technology. You will create reusable data and machine learning products that help teams across the business discover, trust, and use data.
Design, build, and own reliable, scalable, well-documented data products, pipelines, and datasets for other teams to use.
Apply software engineering practices such as testing, version control, and CI/CD to production data and machine learning systems.
Build reusable machine learning products, including document processing, transaction coding suggestions, and retrieval-augmented or agentic tools.
Establish data quality checks, monitoring, alerts, and service-level expectations for data products.
Partner with data consumers to understand their needs, gather feedback, and improve products over time.
Work with analytics and business intelligence teams to make data easier to find, understand, and use independently.
Improve the data platform and expand the suite of products available to other teams.
At least 5 years of experience in data engineering, software engineering, or DevOps.
Advanced Python and Go skills, or Java experience, along with strong SQL.
Experience with a workflow orchestrator such as Airflow, Dagster, or Prefect, and a data platform such as Snowflake, Databricks, BigQuery, or HDFS-based systems.
Experience building data infrastructure on GCP, AWS, or a similar cloud platform, including services on Kubernetes and infrastructure managed with Terraform or Pulumi.
A track record of building reusable data products for other teams. Experience developing a data platform or product suite from the ground up is beneficial.
Production machine learning or RAG and agentic system experience, including vector databases, is beneficial.
Knowledge of data modeling approaches or streaming systems is beneficial.
Salary range: β¬70,000 to β¬95,000 annually. Equity and visa sponsorship details were not provided.
Remote within Europe.
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