Senior Data Engineer role at AI & Data Engineering focused on Databricks engineering.
SF
Hybrid Principal Quant Data Engineer
Posted 3 months ago
About the role
- Quant Data Engineer developing Oracle PL/SQL-based risk analytics solutions for Fidelity Asset Management Technology. Collaborating with multiple teams for database engineering and optimization efforts.
Responsibilities
- Lead the design and development of Oracle PL/SQL database processes, procedures, and packages to support investment risk analytics
- Architect scalable and efficient database solutions for high-volume, time-sensitive risk data
- Collaborate with risk managers, quantitative analysts, and engineering teams to gather requirements and deliver robust data solutions
- Own performance tuning, query optimization, and troubleshooting of production database issues
- Ensure data integrity, quality, and governance across systems
- Drive modernization efforts, including migration from legacy systems and adoption of best practices
- Define and enforce database development standards and documentation
- Act as a strategic partner in planning long-term data architecture and infrastructure initiatives
- Apply validated quality software engineering practices through all phases of development
- Ensure resilience and stability through quality code reviews, unit, regression and user acceptance testing, dev ops and level two production support
- Provide mentorship and technical guidance to junior developers
Requirements
- 10+ years of hands-on experience in Oracle PL/SQL development and database engineering
- Proven expertise in designing and implementing complex database solutions in a production environment
- Strong understanding of relational database design, indexing strategies, and performance optimization
- Experience working with investment risk systems or financial data is highly preferred
- Excellent communication and stakeholder management skills
- Ability to lead cross-functional initiatives and work independently
- Familiarity with tools such as Jira, Git, and CI/CD pipelines
- Experience with data modeling and ETL frameworks
- Exposure to Python or other scripting languages for data integration
- Knowledge of cloud-based database solutions (e.g., AWS RDS, Snowflake) is a plus
- Understanding of financial instruments, risk models, or portfolio analytics is beneficial
Benefits
- comprehensive health care coverage and emotional well-being support
- market-leading retirement
- generous paid time off and parental leave
- charitable giving employee match program
- educational assistance including student loan repayment, tuition reimbursement, and learning resources to develop your career
Job title
Job type
Experience level
Salary
Degree requirement
Tech skills
Location requirements
Senior Data Engineer at Yü Group responsible for leading data engineering team and optimizing data solutions within the energy sector.
Data Engineer managing payment processing and data accuracy while collaborating with financial teams. Building and optimizing data pipelines for transactional data in a hybrid work environment.
Data Engineer building analytical tools for Dry Bulk market data operations at Kpler. Join a team of over 700 experts transforming data into actionable strategies.
Data Engineer developing tools for maintaining data integrity in cargo tracking at Kpler. Collaborating with analysts and engineers to enhance data quality management.
Lead Azure Data Engineer designing and optimizing data ecosystems on Microsoft Cloud. Responsible for building scalable data platforms and pipelines for analytics and reporting.
Data Engineer providing support for IBM DataStage ETL jobs at Callibrity. Collaborating with stakeholders and working to modernize technology solutions in a hybrid work environment.
Cloud Data Engineer implementing tailored solutions for Volkswagen Group data processing. Building ETL/ELT pipelines while collaborating with technical experts.
Data Engineer responsible for building scalable data infrastructure that supports data - driven decisions. Collaborating with team to maintain systems and unlock data value for organizations.
Data Engineer designing and optimizing data pipelines using Databricks and Google Cloud Platform. Collaborating with analysts and scientists to deliver high - quality data products.