Data Engineering Manager

2 days ago

Houston, Texas, United States Phaxis Full time
About the Role

We are seeking an experienced Data and Cloud Platform Engineering Manager to join our team at Phaxis. As a key member of our technology team, you will be responsible for designing, implementing, and maintaining our cloud infrastructure, application platforms, development tooling, and data architecture.

Key Responsibilities
  • Architect and develop platform components, frameworks, and offerings
  • Build infrastructure to make data sets accessible and useful
  • Develop tools and processes for acquisition, validation, organization, and storage of large volumes of structured and unstructured data from many sources
  • Develop systems to improve and test data quality
  • Support and educate team members on best practices in software engineering and participate in code reviews
  • Establish a strong software engineering culture and high code quality standards
  • Produce documentation for technical and non-technical audiences
  • Provide leadership for the team by providing feedback on code, behavioral challenges, and other work items
  • Manage systems efficiently at scale through standardization, automation, testing, and monitoring
  • Enforce standards for all phases of software development cycle including source control and testing
  • Work with business owners to regularly re-prioritize projects while delivering both tactical and long-term objectives
  • Develop well-defined processes for integrating new technologies to meet both business and technical needs
  • Drive the elimination of operational tasks through automation and self-service
  • Drive efficient utilization of resources through metrics and reporting
  • Manage multiple environments and promote code between them
  • Implement standardized methodologies and CI/CD tooling that automate testing, builds, and deployment
Requirements and Skills
  • Strong background in software and data engineering with 10+ years of experience
  • Strong Python knowledge including OOP
  • Broad knowledge and experience with relational databases (stored procedures, indexing, partitioning, table design, query optimization, and design) with proficiency in SQL
  • Exposure to data warehouses (snowflake, redshift)
  • Strong knowledge of cloud environments (preferably AWS, ideally exposure to both windows and Linux), including security, networking, and infrastructure as code (Terraform)
  • Experience with automation/orchestration platforms (Airflow)
  • Extensive experience with version/source control systems (Git)
  • Exposure to commodities and weather markets, including electricity, congestion markets, natural gas, oil, and emissions and related data sets (ISO APIs, fundamental data vendors, government APIs)
  • Strong financial and fundamental data knowledge and experience working with large datasets
  • Ability to execute independently, on a deadline, and under pressure
  • Experience with deploying monitoring and alerting solutions
  • Experience with designing and implementing data pipelines for quality, acquisition, validation, and related infrastructure
  • Experience in a front office development role, preferably on a trading desk. supporting Trading and Risk Management systems
  • Communication skills and project management experience
  • Excellent troubleshooting and analytical skills
  • Experience in data visualization and web user interfaces is a plus
  • Exceptional attention to detail
  • Ability to understand unfamiliar code bases (multi and mono repo structure) and debug applications
  • Experience managing a team of developers
  • Experience designing and architecting libraries
  • Knowledge of derivative pricing, products, and markets
  • Consistent track record managing and balancing priorities across a diverse set of stakeholders and guiding them toward strategic solution
About Phaxis

Phaxis is a boutique analytics-focused hedge fund with a strong commitment to innovation and excellence. We are looking for talented individuals who share our passion for technology and data-driven decision making.

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