Design and develop modern data services for fraud detection, building scalable pipelines, data models, and migration solutions within a cloud‑based environment.
About the role
Key Responsibilities
Design, build, and maintain robust data pipelines to ingest, transform, and store fraud‑related data.
Develop and optimize data models and warehouses to support analytics and reporting needs.
Collaborate with fraud analysts and application teams to translate business requirements into technical solutions.
Implement data migration strategies and ensure data quality and integrity across systems.
Leverage cloud services (e.g., AWS) to scale data infrastructure and improve performance.
Requirements
Bachelor's or Master's degree in Computer Science, Engineering, or a related field.
2+ years of hands‑on experience in data engineering, including ETL development and data warehousing.
Proficiency in SQL and a programming language such as Python.
Experience with cloud platforms (preferably AWS) and modern data storage technologies.
Strong analytical skills and ability to work cross‑functionally in a fast‑paced environment.