About the Role :
We are looking for an experienced Lead Data Analyst with a strong background in Private Equity and modern data warehousing tools like Snowflake. The ideal candidate will play a strategic role in driving data initiatives, enabling data-driven decision-making, and optimizing analytics infrastructure for our investment operations. This is a senior-level role requiring both technical expertise and domain acumen in private equity and fund analytics.
Key Responsibilities :
- Serve as the subject matter expert (SME) in Private Equity data analytics, working closely with investment, finance, and operations teams to drive insights and reporting
- Design, develop, and maintain data pipelines, models, and warehouses using Snowflake and other modern tools
- Lead data strategy initiatives, standardize data processes, and ensure data governance across private equity portfolios and fund structures
- Partner with business users to gather reporting requirements and translate them into scalable dashboards using tools like Power BI or Tableau
- Mentor junior analysts, review code, and set best practices for analytics and reporting
- Enable automated data ingestion, transformation, and validation workflows across multiple data sources (deal flow, fund performance, investor reporting, etc.)
- Collaborate with engineering, product, and compliance teams to support data needs for audits, valuations, and performance metrics
- Identify and resolve data quality issues, driving continuous improvement in data accuracy and timeliness
- Manage stakeholder communication across departments and geographies
Key Requirements :
15+ years of professional experience in data analytics, business intelligence, or data engineering rolesProven domain expertise in Private Equity, including familiarity with fund structures, capital calls / distributions, IRR / MOIC calculations, and investor reportingDeep hands-on experience with Snowflake, including writing performant queries, managing schemas, and leveraging Snowpipe / Streams / TasksAdvanced proficiency in SQL and data modeling techniquesExperience with ETL tools (e.g., dbt, Informatica, Talend) and scripting languages like PythonStrong dashboarding skills using Power BI, Tableau, or similar platformsUnderstanding of regulatory and compliance requirements in financial services data environmentsExcellent communication and stakeholder management skills, with a strategic mindsetExperience leading data teams and cross-functional projectsPreferred Qualifications :
Bachelors or Masters degree in Computer Science, Finance, Data Science, or a related fieldExperience with cloud platforms (AWS, Azure, or GCP)Familiarity with data cataloging, lineage, and data governance toolsKnowledge of API integrations with third-party PE systems like eFront, Burgiss, or Investranref : hirist.tech)