The Role
Tidemark is a growth equity firm purpose-built to help companies win & scale. Tidemark is powered by a community of investors, entrepreneurs, and operators who are energized by ideas, a love of competition, and the drive to give back. We make investments of $20 -150M to support the next generation of category leaders.
Tidemark is looking for an Analytics engineer who excels in:
- Building distributed systems, ETL pipelines, data science & automation frameworks across the investing workflow - sourcing, diligence & portfolio support.
- Continuous learning and taking ownership of challenging technical problems with both a PM & Investor mindset.
- Working with a high-performing, nimble Investing team who are looking to build a fully-fledged data science & automation platform.
You will thrive in this role if you are driven by tackling unsolved technical challenges and inspired by the idea of building out a data & software driven investment platform.
Responsibilities
- Design, build, and maintain the data infrastructure necessary for optimal extraction, transformation, and loading of data from a variety of data sources using SQL, NoSQL, and big data technologies
- Develop and implement data collection systems that integrate a variety of sources such as proprietary company data, publicly available data on the web & commercial data from various data vendors
- Build processing logic and analytics tools that utilize the data pipeline to provide actionable insights through query workflows and data visualizations
- Explore and implement cutting-edge machine learning tools including company scoring and fine-tuned LLMs to optimize investor efficiency
- Collaborate closely with the investment team and external stakeholders (founders, management teams, fellows, limited partners) to continuously improve our product
Required qualifications:
- Bachelor's or master's degree in Computer Science, Data Science or a related field.
- Experience of minimum 2-3 years as a full stack engineer, data scientist, analytics engineer & data engineer, with experience in data modeling, data warehousing, and building and maintaining ETL pipelines