Define the roadmap, develop and manage architecture, technical solutions and lead engineering teams for the next generation of data products, applications and services for the fraud team.
The leader will drive automation in order to scale the fraud teams ability to address fraud more efficiently.
What You’ll Do :
Drive and deliver on the infrastructure focusing on Engineering best practices and efficiency with defined measurable KPIs.
Lead agile engineering teams to deliver end-to-end technical solutions that exceed product expectations.
Grow the data engineering team and design team to scale, improve effectiveness of the Engineering teams through coaching, mentoring.
Delivery Oversight, Tech oversight - guidance, reviews, modernization.
Drive the design, building, and launching of new data models and data pipelines in production.
What You Need to Succeed :
Bachelors degree preferably in engineering, computer science, mathematics, information systems, data analysis
10+ years of data engineering experience
Deep Technical proficiency in SQL, Python
Experience in data processing using traditional and distributed systems (e.g., Hadoop, Spark, Dataflow, Airflow).
Experience designing data models and data warehouses and using SQL and NoSQL database management systems.
Able to identify the root cause of problems and identify, propose, and recommend innovative solutions
Ability to scale, automate, and enhance data processes to streamline efficiencies
Experience writing and maintaining ETLs which operate on a variety of structured and unstructured sources.
Experience in large scale distributed data processing