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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
  • Programming (Python and SQL knowledge preferred)
  • Cloud architecture (e.g., AWS, GCP)
  • Working with data at scale (e.g., Pandas, Data Warehouses)
  • Prior experience with any of the following is a plus:
  • Container orchestration (e.g., Docker, Kubernetes, Airflow)
  • Automated data acquisition (e.g., Scrapy)
  • Machine learning, NLP, and/or ML-ops
  • Cloud DevOps
  • 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.