Software Development Manager, Data Engineering
Houston, Texas, United States
Since 2001, our software engineers have helped tackle the complex and interesting challenge of discovering value hidden in the world’s data. We are pushing the technical envelope to solve these problems, and in the process are helping to redefine investment management and other fields. As the world of data continues to grow exponentially, the issues they address will only increase in difficulty, scale and excitement.
In order to meet these challenges, we’ve built a data accumulation platform that allows us to ingest over 10 terabytes of data per day, and a custom distributed storage solution to store the over 50 petabytes of information we’ve accumulated since our inception. We’ve also built an entire suite of analysis tools that enable our quantitative researchers to utilize this data to produce predictive models that help us automatically invest each and every day.
This model-driven, technology-fueled approach to investing not only gives us a long-term advantage over old-school investors – it has also created a whole set of technical problems to solve that don’t always have an obvious solution. This gives you the ongoing opportunity to build proprietary solutions and/or bring to bear the best open source options the market. We have created a robust infrastructure that empowers all of our engineers, and you will work within a collaborative work culture that ensures that a great idea can come from anywhere.
Problems at our level of complexity require you to possess a passion for learning as well as deep understanding across a wide array of technical competencies. We’ve attracted technologists who possess special capabilities in a wide variety of domains including data transformation and visualization, performance optimization, cloud computing, and distributed systems. While we face large-scale problems, we hire only the best to take them on. This enables us to keep your team size small and your individual impact significant.
- Curate massive amounts of data for thousands of different tradable instruments, including stocks, bonds, futures, contracts, commodities, and more;
- Manage the design and development of engineering solutions for supporting structured datasets
- Manage an on-going support rotation to ensure continual availability of our software and datasets
- Perform manual steps and develop programs and processes to perform statistical/quantitative analysis on datasets to ensure completeness and integrity;
- Coordinate project-related work with researchers and others on the engineering and business teams;
- Be part of a team to support the data used by production trading algorithms.
- Bachelor in Computer Science (Master’s/PhD is a plus)
- 10+ years of relevant experience in software development with demonstrated progression from hands-on experience to management roles
- 5+ years of experience managing production software engineering teams
- A proven track record of managing, developing, and mentoring software engineering teams and driving projects to completion
- Familiarity with working in an agile environment, delivering incremental features aligning with a long term product mindset
- Extensive experience developing in-house software solutions
- Experience in full-cycle product development
- Experience and ability in making (and being held accountable for) rapid mission-critical decisions in a continually evolving environment
- Experience in business administration or finance (MBA a plus)
- Experience working on data-related challenges, data engineering such as data processing pipeline, data serving infrastructure, storage/query engine, data quality measurement/monitoring, and data visualization
- Some experience and knowledge on data infrastructure, storage, framework, tools such as Hadoop, Spark, Cassandra, MongoDB, Elastic Search, SQL, etc.
- A plus if have some experience with public cloud technology such as Amazon Web Services (AWS), Azure, Google Cloud.
- A plus if have experience in machine learning, data mining such as NLP, classification, clustering, etc.