Select Equity Group was founded in 1990 on the premise that rigorous, independent research and disciplined, long-term investing will generate superior returns for our clients. Today, the Firm has over $30 billion in assets across long-only and long/short strategies utilizing a team-based approach and centralized research effort. Our global client base includes endowments, foundations, public and private pensions, private banks, family offices and high-net-worth individuals. Our more than 180 employees possess diversity of thought, experiences and backgrounds and share a commitment to our Core Principles (below). Our employees thrive in a collaborative environment that empowers them to apply curiosity, creativity and continuous improvement in pursuit of differentiated excellence for our clients.
Commitment to Giving Back: The Select Equity Group Foundation, established in 2000, makes a positive impact by actively engaging all employees in identifying and supporting charitable organizations of excellence.
Location: Select Equity Group’s corporate office is based in New York City.
The Data Engineer will be part of a growing Data team and reports to the Head of Data and Analytics. His/ her primary responsibility is to develop innovative/scalable ways to ingest, process, and analyze data – enabling the data, quantitative, and risk teams to generate deep and unconventional investment insights for companies of interest.
The ideal candidate is an entrepreneurial self-starter who is passionate about continuous learning in a rapidly evolving data science space. Extreme technical competence, intellectual curiosity, and attention to detail are essential, as are flexibility and comfort working in a growing organization.
• Sourcing data: supporting technical vendor due diligence (e.g., assessing data quality, systematic backtesting against fundamental metrics); developing bespoke in-house data acquisition programs; interfacing with vendors to ingest data into our cloud-based infrastructure
• Featuring/analyzing data: developing in-house algorithms to process data (e.g., sentiment analysis, product matching, SQL enrichment)
• Infrastructure development and maintenance: creating custom solutions to continuously monitor data pipelines; maintaining cloud infrastructure and platforms across data, quant, and risk teams; interfacing with on-prem solution for migration to the cloud; continuous due diligence of new technologies for introduction to the Firm
• Application development: developing bespoke web-based applications to facilitate data adoption within investment research
• Bachelor’s degree in Engineering or Computer Science or Math with a minimum 3.6 GPA
• Prior experience with the following
o Programming (Python and SQL knowledge preferred)
o Cloud architecture (e.g., AWS, GCP)
o Working with data at scale (e.g., Pandas, Data Warehouses)
• Prior experience with any of the following is a plus:
o Container orchestration (e.g., Docker, Kubernetes, Airflow)
o Automated data acquisition (e.g., Scrapy)
o Machine learning, NLP, and/or ML-ops
o Cloud DevOps
o Concepts in statistics (e.g., regressions, predictive models, tests of significance)
• Excellent interpersonal and communication skills
• Track record of continuous learning
• Demonstrated passion for data, although past experience not required
• Highest degree of integrity, professionalism and confidentiality
• Fit with Select Equity’s Core Principles (below)
• Originality: We generate our own ideas and never deploy common practice without skepticism. We strive to avoid the herd.
• Innate Curiosity: There are no dumb questions. We challenge universally accepted beliefs and seek new angles of understanding.
• Charity: We recognize our good fortune and give back to society in meaningful and thoughtful ways.
• Continuous Improvement: We always strive to improve our performance and measure ourselves absolutely, not relatively.
• Humility: We seek no acclaim individually or as a Firm other than earning the gratitude of our clients.
• Teamwork: We trust our colleagues and communicate with transparency and respect. Ours is a culture of giving credit, not seeking credit.