System Engineer US L4

Charlotte, NC, United States (On-site) Contract (5 months 12 days) Published 11 hours ago debugging apache spark data governance Docker & Kubernetes AWS and Azure data engineering Python sql database etl

• Our financial services client oversees within a large US bank with presence internationally the Data Pipelines and Automation Services within a Chief Data Office
• The team our client is leading is responsible for enterprise data platform modernization initiatives spanning data movement automation platform engineering and operational transformation
• The client is responsible for the bank for enterprise ETL platforms data pipeline frameworks and automation services that enable secure governed and scalable data delivery across hybrid cloud environments
• The team is executing strategic modernization programs including legacy platform retirement cloud native platform adoption containerization CICD implementation and operational process automation
• The team for this project is leading the development of a green field best of breed from scratch next generation enterprise data pipeline platform that unifies data engineering standards governance lineage and deployment across multiple data processing technologies and environments
• The project team is building a platform to unify data pipeline execution across the enterprise and leading greenfield platform that requires for engineer roles on the team a strong understanding of APIs Python Sparkflow DocketK8s Automated CICD with Github Actions or other tools composable services data governance and distributed systems The goal is to turn complex systems into clean reusable services via Python, * Seeking a System Engineer US L4 to support a greenfield platform initiative with a focus on building integrations with Spark Engine and Spark Flow, * Design and develop scalable integrations with Spark Engine and Spark Flow for the Unity platform
• Develop and consume RESTful APIs and services to enable seamless system interoperability
• Work with largescale distributed compute frameworks to process and manage high volume data
• Drive performance tuning optimization and scalability improvements

• This role requires strong expertise in system design and development distributed computing and API integrations along with the ability to work independently with minimal guidance in a highly regulated enterprise environment, * Experience with Apache Spark Spark Engine Spark Flow
• Familiarity with big data ecosystems Hadoop Hive SQL Kafka
• Exposure to cloud platforms AWS Azure or GCP
• Hands-on experience building and integrating APIs and microservices
• Strong problem solving and debugging skills

The pay range that the employer in good faith reasonably expects to pay for this position is $33.63/hour - $52.55/hour. Our benefits include medical, dental, vision and retirement benefits. Applications will be accepted on an ongoing basis.