Coatue Management | New York, NY | Infrastructure Engineer, Data Engineer | Fulltime | ONSITE
Coatue Management is a long/short equity hedge fund based in New York City. We focus on investments in the technology, media and telecommunications sectors and manage $10+ billion in assets on behalf of individuals, nonprofit organizations and institutional investors.
We’re in the middle of building a market intelligence platform based on non-traditional data (ie. Non-financial data). We look for unique and creative sources of data (everything from e-commerce pricing to satellite data), use it to model key firm and economic metrics, and present it to investment staff.
We’re seeking an engineer interested in taking a lead role in building a data pipeline and warehousing backend for datasets ingested from APIs, web scraping, remote databases, and purchased data feeds. You would help build systems for job scheduling, data anomaly/QA detection, process monitoring, and efficient storage/querying. Our current infrastructure uses Python, MySQL, and Docker but we are open to well thought out alternatives. The ideal candidate will have experience and opinions on database architecture and best practices when building high throughput data systems. This role offers the opportunity to take ownership of the architecture and offers technical freedom/creativity.
Nontraditional data is THE future of investing and engineers are best suited to find it. For instance, if you wanted to know who was spending the most to acquire users, wouldn't it make sense to get bid data from ad exchanges? If you wanted to know which were the most anticipated games of the year, wouldn't the Reddit API be the tool you'd use to check? And if you wanted to predict crop yields, wouldn't satellite data of crop fields be the most realtime way to see it? Traditional equity research doesn't do this - but we do and we've seen it work. We're building a system to systematize our capabilities.
The scale of what we're trying accomplish is no easy feat - we handle realtime data at very high throughputs and analyze datasets > 1TB in an environment where accuracy and speed counts. Our output has a real impact on investment decisions.
Coatue Management is a long/short equity hedge fund based in New York City. We focus on investments in the technology, media and telecommunications sectors and manage $10+ billion in assets on behalf of individuals, nonprofit organizations and institutional investors.
We’re in the middle of building a market intelligence platform based on non-traditional data (ie. Non-financial data). We look for unique and creative sources of data (everything from e-commerce pricing to satellite data), use it to model key firm and economic metrics, and present it to investment staff.
We’re seeking an engineer interested in taking a lead role in building a data pipeline and warehousing backend for datasets ingested from APIs, web scraping, remote databases, and purchased data feeds. You would help build systems for job scheduling, data anomaly/QA detection, process monitoring, and efficient storage/querying. Our current infrastructure uses Python, MySQL, and Docker but we are open to well thought out alternatives. The ideal candidate will have experience and opinions on database architecture and best practices when building high throughput data systems. This role offers the opportunity to take ownership of the architecture and offers technical freedom/creativity.
Keyword skills: Data Engineer, Python, AWS, SQL, Docker, Redis, Redshift, Spark
We're always happy to talk to data scientists interested in creative ways of measuring the economy as well.
Email us if you're interested or want to learn more: recruiting [at] coatue.com