Job Description SummaryThis position will be a hybrid work arrangement. You will receive 18 remote workdays per quarter to use at your discretion, subject to manager approval. For example, you may choose to work in the office 4 days per week and take one remote day weekly (typically 13 weeks per quarter), leaving 5 additional remote days to be used as needed.
About Investment Data and AnalyticsOur organization's mission is to build technology that lets the firm systematize and scale its understanding of private markets and management of our funds. Our team works side-by-side with investors and quantitative researchers to innovate technology-driven investment processes; solve broad industry problems ranging from AI driven digitization of unstructured data to systematic monitoring of private equity portfolios.
The Associate role combines hands-on engineering execution with the opportunity to build deep expertise in private markets data. Working under the guidance of senior engineers, you will develop, test, and operate the pipelines and datasets our investment and research teams rely on - taking on progressively more complex ownership as your technical and domain judgment grows.
What you will do: - Data engineering - build, test, and deploy pipelines and transformations across financial/economic datasets using modern data stacks.
- Infrastructure/platform engineering - run and monitor production data workflows, troubleshoot failures, and implement alerting, logging, and automated testing within CI/CD.
- Data Quality - develop validation and reconciliation checks, monitor pipeline health through KPIs, and own root-cause analysis for data issues.
- Collaboration - partner with data engineering, DevOps, application, and investment teams to clarify requirements and deliver well-documented solutions.
- And ... Problem solving - perform deep data analysis to support investment model research and identify manual processes worth automating.
What you bring: - Demonstrated ability in data engineering and analysis, including data-centric testing and deployment of FinTech applications.
- Proficiency in SQL (MSSQL or equivalent RDBMS) and Python, with experience building ETL pipelines for large datasets.
- Experience with DBT and Azure Data Factory and Pipelines; exposure to Snowflake, MS Synapse, or Power BI a plus.
- Strong analytical, organizational, and problem-solving skills with outstanding attention to detail, a genuine interest in financial markets, and comfort working in a scrum/agile SDLC environment.
Education Preferred - Bachelor of Science (B.S) or equivalent in Computer Science
- Master of Science (M.S) or equivalent in Computer Science
Experience - 3-5 Years of Data Engineering or Data Operations experience preferred
- Exposure to private equity or investment management data, partnering with product, application, and operations teams
#LI-Hybrid
Base Salary Range$145,000.00 - $175,000.00
This USD base salary range represents only one component of total compensation for this role and is provided in accordance with local requirements. This role is eligible for a discretionary annual bonus, which is determined based on individual and overall firm performance. In addition to salary and bonus, total compensation may include eligibility for long-term reward programs and a comprehensive total rewards package that may include retirement, health, insurance, paid time off, and wellness programs. Our total rewards offerings are influenced by several business factors, and eligibility for certain components will vary by position and geography. Please note the posted ranges do not apply outside the U.S. and should not be converted to other currencies as a proxy for compensation in other countries.
