Design and implement real‑time data pipelines that power fraud detection and operational decision making.
Build robust ELT workflows from source ingestion through to data presentation for internal stakeholders.
Develop event‑driven solutions using technologies such as Apache Kafka and Apache Flink.
Write high‑quality, testable, maintainable code in Python or Java, with strong SQL capability.
Contribute to solution design, code reviews, automated testing, and documentation.
Apply industry‑leading engineering standards with a focus on code quality, consistency, and resilience.
Build and maintain cloud infrastructure using AWS and Infrastructure‑as‑Code tooling (CloudFormation/Terraform).
Own deployment and operational support across development, test, and production environments.
Champion continuous improvement across tooling, processes, and engineering practices.
Partner closely with developers, product owners, scrum masters, and analysts to ensure data enables an exceptional client experience.
Participate fully in agile ceremonies including sprint planning, daily scrums, reviews, and retrospectives.

5+ years of experience as a data engineer
Strong proficiency in Python or Java, SQL, cloud environments (preferably AWS)
Hands-on experience with Kafka and streaming frameworks such as Flink
Proficiency with data transformation tools (PySpark, Pandas)
Familiarity with data quality frameworks (e.g., Great Expectations)
Experience with graph databases is a plus
Exposure to building cloud infrastructure via IaC
Excellent communication skills, able to translate complex topics for technical and non‑technical audiences
Understanding of agile development; scrum experience preferred
A continuous learning mindset and willingness to expand both technical and non‑technical skills.
A degree in a STEM field is beneficial but not required.

Senior Data Engineer – Anti-Fraud Technology

Key skills