Data Analyst, Partnership Strategies
Data Analyst, Partnerships Strategies
Tier 1 Investment Firm
Boston - Hybrid (3/2)
FTE
Our leading investment client is looking for a skilled Data Analyst to join a dynamic and growing data and engineering team, supporting a broad range of investment strategies. This role involves designing and developing critical technology assets, leveraging cloud-based solutions to build scalable data pipelines and storage architectures. The ideal candidate will have a strong technical foundation in Python, SQL, dbt, and cloud platforms (preferably AWS), along with experience in data visualization tools like Streamlit, Plotly, Power BI, or Tableau. This is a unique opportunity to contribute to an early-stage data environment within an investment firm that operates across diverse asset classes, including commodities, fixed income, equities, derivatives, and cryptocurrencies.
As part of a highly collaborative and fast-moving team, the Data Analyst will be responsible for sourcing, structuring, and analyzing complex datasets—both structured and unstructured—to support investment decision-making. The role requires proficiency in relational databases (PostgreSQL preferred), data pipeline management, and software development lifecycle best practices. Hands-on experience with Git, CI/CD processes, Airflow, and Docker is a plus. Additionally, a familiarity with web scraping technologies and Kimball/Star schema data warehousing design would be advantageous. Candidates should demonstrate an ability to think critically, solve problems independently, and adapt quickly to evolving priorities.
This position offers a high level of exposure to experienced investors and portfolio managers, with projects executed in small cross-functional teams. The ideal candidate is not only technically proficient but also able to translate business needs into technical solutions and effectively communicate with non-technical stakeholders. Prior experience in Financial Services, Economics, or Accounting is a plus but not required. A strong analytical mindset, keen attention to detail, and a passion for leveraging data to drive investment insights are essential qualities for success in this role.
Candidates should have a BS or MS degree in Computer Science (or a related field) and 2–5 years of experience developing software applications. A demonstrated ability to learn new technologies and tools—such as GitHub Copilot or AI-driven development platforms—is highly desirable. This role is ideal for a self-motivated problem solver who thrives in a collaborative, high-impact environment and is eager to work on complex challenges at the intersection of data, finance, and technology.