About
The Role In this role, you will take ownership for building and operating our data architecture to support new and evolving fraud solutions. You’ll play a key role in ensuring data is reliable, scalable, and accessible to power models, agents, and UIs directly impacting our customers’ ability to detect and prevent fraud. This is an opportunity to work on production systems with real‑world impact while continuing to grow your skills in data engineering, cloud platforms, and distributed systems.
Responsibilities
Design, build, and maintain scalable data pipelines and workflows in a cloud environment
Deliver clean, well‑structured datasets to support fraud analytics, machine learning models, and agentic solutions
Contribute to improving our data architecture, including ingestion, storage, and access patterns
Own data operations by monitoring data workflows, triaging failures, and resolving data issues
Enhance observability and performance by implementing monitoring and optimizing pipelines for reliability, scalability, and cost efficiency
Partner with product managers, data scientists, and engineers to translate fraud and risk requirements into data solutions
Write maintainable code; participate in code reviews; and help improve testing, deployment, and documentation standards
Production Support: review production data pipeline executions, investigate and resolve failures
Development: build and orchestrate data pipelines, defining data flow, transformations, and dataset relationships
Observability: monitor and optimize data pipelines for performance and efficiency
Collaboration: work closely with teams and stakeholders to understand data requirements and ensure platform solutions meet business needs
Requirements Must Haves
Typically requires a Bachelor’s degree in a relevant field and a minimum of 2 years of related experience; or an advanced degree without experience; or equivalent work experience.
Experience building and maintaining data pipelines and workflows in production environments
Proficiency in SQL and working with relational and/or analytical data stores
Experience with Python
Familiarity with data modeling, transformation, and orchestration concepts
Experience with data warehouses and distributed data processing systems
Experience with version control (e.g., Git) and CI/CD practices
Ability to troubleshoot data issues, debug pipelines, and work through ambiguous problems
Nice to Have
Experience with tools such as Apache Airflow, dbt, Kafka, Airbyte, or FiveTran
Experience with Snowflake or similar cloud data warehouses
Experience with SQL Server, PostgreSQL, or NoSQL systems like DynamoDB
Familiarity with infrastructure as code tools (e.g., Terraform)
Experience with Docker and/or Kubernetes
Exposure to platforms like Databricks, AWS Glue, AWS SageMaker, Snowpark
Health & Wellness
Hybrid Work Opportunities
Flexible Time Off
Career Development & Mentoring Programs
Health & Wellness Benefits, including competitive health insurance offerings and generous paid parental leave for eligible new parents
Community Volunteering & Company Philanthropy Programs
Employee Peer Recognition Programs – “You Earned it”
We are an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, genetic information, or veteran status.
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Languages
- English
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