Cloud engineer • miami fl
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The average salary range is between $ 120,000 and $ 180,375 year , with the average salary hovering around $ 140,000 year .
The average salary range is between $ 110,421 and $ 167,056 year , with the average salary hovering around $ 131,648 year .
Millennium is a top tier global hedge fund with a strong commitment to leveraging innovations in technology and data science to solve complex problems for the business. We are assembling a strong Commodities Technology team to build our next generation in-house Commodities platform. Commodities Technology provides a dynamic and fast-paced environment with excellent growth opportunities.
Responsibilities
Work closely with quants, portfolio manager, risk managers and other engineers in New York, Chicago, Miami, and Bangalore to develop data intensive and multi-asset analytics for our Commodities platform
Gather requirements and user feedback in collaboration with fellow engineers and project leads
Design, build and refactor robust software applications with clean and concise code following Agile and continuous delivery practices
Automation of system maintenance tasks, end-of-day processing jobs, data integrity checks and bulk data loads/extracts
Staying abreast of industry trends, new platforms and tools, and coming up with a business case to adopt new technologies
Develop new tools and infrastructure using Python (Flask/Fast API) or Java (Spring Boot) and relational data backend (AWS – Aurora/Redshift/Athena/S3)
Support users and operational flows for quantitative risk, senior management and portfolio management teams using the tools developed
Qualifications/Skills Required
Advance degree in computer science or any other scientific fields
3+ years of experience in CI/CD Tools like TeamCity, Jenkins, Octopus Deploy and ArgoCD.
AWS Cloud infrastructure design, implementation and support. Experience with multiple AWS Services.
Infrastructure as Code deploying cloud infrastructure using Terraform or Cloudformation.
Knowledge of Python (Flask/FastAPI/Django)
Demonstrated expertise in the process of containerization for applications and their subsequent orchestration within Kubernetes environments.
Experience working on at least one monitoring/observability stack (Datadog, ELK, Splunk, Loki, Grafana).
Strong knowledge of Unix or Linux
Strong communication skills to collaborate with various stakeholders
Able to work independently in a fast-paced environment
Detail oriented, organized, demonstrating thoroughness and strong ownership of work
Experience working in a production environment.
Some experience with relational and non-relational databases.
Qualifications/Nice to have
Experience with a messaging middleware platform like Solace, Kafka or RabbitMQ.
Experience with Snowflake and distributed processing technologies (e.g., Hadoop, Flink, Spark)
