Omega Point empowers the institutional investment community with a modern, factor-based portfolio analytics decision-making system. Enhanced by the latest advancements in machine learning and AI, Omega Point's cloud platform ensures fast, painless integration and seamless fit across the widest range of investment processes. We enable a variety of portfolio analytics and portfolio construction workflows, including factor analysis, trade simulation, optimization, hedging and thematic investing. Omega Point clients include top fundamental asset managers, hedge funds, and institutional allocators worldwide. The firm is headquartered in San Francisco with offices in New York and Quebec City.
Omega Point offers you...
- A competitive salary and benefits package
- Flexibility to telecommute (and not only during the pandemic)...
- ...or come and work at the Quebec City, New York, or San Francisco offices.
- A great environment with a talented team
- A remote-first culture we've built from the ground up to have a distributed workforce
- One or two summits per year (in-person, post-pandemic) where you can meet the whole team in person and do team building activities. Some of the latest destinations: Miami Beach, Austin (Texas), San Francisco
- Comprehensive health insurance for you and your family
- Great perks including a work-from-home setup budget, unlimited vacation, 401k, flexible hours, and education/certification benefits
Omega Point embraces diversity and equal opportunity in a serious way. We are committed to building a team that represents a variety of backgrounds, perspectives, and skills. The more inclusive we are, the better our work will be.
As a Data Engineer, you will use your skills at manipulating large datasets to provide valuable data to our platform customers. You will be responsible for designing and implementing improvements to our data pipeline, including data ingestion, data cleaning, and data processing. You will then build systems that will integrate that data with data from other partners and our customers to provide impactful insights to our users.
- Design and implement solutions for data ingestion, data transformation, and data management
- Develop processes to validate the integrity of data as it comes into our system
- Assist with occasional research projects as we investigate new ways to provide value to our customers
- Collaborate with data scientists, operational engineering, and application developers to build and maintain fast, reliable, and efficient solutions for automating our data lifecycle
- Stay up to date on tools and trends in the data engineering space in order to advise on and advocate for proposed changes
- Provide top-level support for our customer success team if customers have questions about our data or processes
- 3 or more years of building data solutions
- Strong experience in developing data ingestion, data processing, and analytical pipelines
- Experience analyzing and integrating data models from various data sources
- Experience doing data manipulation and calculation in Python, particularly pandas, numpy, scipy (or equivalent in other languages)
- Experience troubleshooting data pipeline issues
- High attention to detail
- Motivation to take initiative and work both independently and in a team environment
- Experience with NoSQL and/or relational databases
- Experience in identifying data validation rules and alerts based on data publishing specifications for data integrity and anomaly detection
- Experience with AWS in general, particularly data-focused technologies, or serverless architectures
- Experience with machine learning or mathematical optimization
- Experience with Golang or Node.js
- Experience in the finance / investment management industry
- Familiarity with factor risk models or equities data is a plus
- Advanced degree in computer science, math, physics, or other quantitative field
- Experience with Agile software development