LexisNexis Risk Solutions is looking to build a best-in-class fraud detection group of products by supporting the day-to-day operations and ongoing development of the Truth Central Data Platform. This involves ensuring consistent and reliable data delivery, troubleshooting production issues, and maintaining the platform architecture.
Requirements
- Current experience in data engineering or a similar technical role
- Current proficiency in using Python and Java
- Experience with big data tools like Apache Spark and Databricks
- Experience working with NoSQL databases
- Solid understanding of data pipeline development and ETL workflows
- Knowledge of Azure fundamentals (or any other cloud platform)
- Familiarity with Infrastructure as Code tools (e.g., Terraform) and CI/CD platforms (e.g., GitHub Actions)
Responsibilities
- Maintaining the Truth Central Data Platform by monitoring the architecture and maintaining or building new data processing pipelines as needed
- Supporting infrastructure and deployment workflows using CI/CD
- Coordinating with Data Engineering to deploy data artifacts into production
- Building and maintaining tools for data validation and quality monitoring
- Troubleshoot production issues, deploy new features, and ensure consistent and reliable data delivery
- Work closely with Implementation Services, client managers, Data Engineering, and Analytics teams
- Help maintain the platform architecture and ensure smooth and reliable operations
Other
- Collaborating with Implementation Services to onboard new clients
- Working with client managers to investigate and resolve data anomalies and production issues resulting from data anomalies
- Partnering with analytics teams to ensure data availability and provide retrospective support
- Strong analytical and problem-solving skills, with experience in Agile environments
- Position is eligible for base salary plus an annual bonus
