Company Description
Our client is a global investment firm, based in Menlo Park, with a mission to achieve the multi-generational goals and aspirations of our clients. Rooted in the endowment style of investing, we seek balanced diversification in order to protect and grow multi-generational capital over the long term. We are committed to the highest professional standards as fiduciaries of our clients' capital and our firm.
We are a collaborative and innovative team that thrives in a fast-paced environment and is committed to generating superior returns for our clients. We value intellectual curiosity, creative thinking, and a passion for using data to drive investment decisions. We foster a culture of mentorship and collaboration, providing opportunities for professional growth and development.
Position Description
We are looking for a full-stack Data Engineer/Scientist. The role involves maintaining and extending scalable data warehouses and data lakes, designing robust data pipelines, and building dashboards and applications to visualize and analyze data
However, there will be opportunities to take on expanded roles depending on the firm’s needs, personal interest and ability to take on more responsibilities:
We’re looking for someone who:
• Has strong problem-solving skills and is an eager, independent learner.
• Displays excellent communication and interpersonal skills.
• Takes initiative and a high degree of ownership and pride in their work.
• Connects with high-level goals and can work effectively with guidance.
• Is curious about new technologies and the investment industry.
• Seeks to understand the broader business (e.g., the clients, their problems, the opportunities).
Responsibilities:
• Assist in maintaining and extending scalable data warehouses and data lakes to support business intelligence and analytics.
• Contribute to the design, development, and implementation of robust data pipelines to collect, transform, and store data from various sources.
• Support operational aspects of our cloud infrastructure.
• Build and maintain dashboards and applications to visualize and analyze data.
• Support the construction and enhancement of quantitative investment tools.
• Provide support to other analysts in their use of data and analytical tools.
• Document data pipelines and processes for knowledge sharing.
• Stay up-to-date on the latest data engineering and data science technologies, actively learning and applying new concepts.
Experience:
• 3-5 years of experience in a data engineering or data science role
• Internal client orientation/mindset and proven experience
• Demonstrated ability to contribute to and support data-driven projects.
• Familiarity with components of the data engineering and data science stack, including:
• Basic understanding of cloud environments and DevOps concepts.
• Experience with data warehousing or data lakehouse architectures (e.g., Databricks, Snowflake).
• Experience with ETL processes and tools (e.g., Airflow).
• Proficiency in programming languages (Python, SQL).
• Experience in building or contributing to analytical applications.
• Experience with data visualization tools (e.g., Power BI, Sigma).
• Familiarity with machine learning libraries (e.g., Scikit-learn) is a plus.
Compensation:
Compensation will be competitive and all cash. If things go well, there will be opportunities for equity in the business.
