Data Analyst - Private Equity

Data Analyst -  Private Equity

About Us

Lantern isn’t your typical fintech start-up. We’re a pioneering Private Equity data intelligence platform with a bold mission: to unleash the power of private markets data as a force for good.

Through our innovative SaaS platform and a passionate team, we’re disrupting the private markets industry by delivering powerful, trusted insights to GPs, LPs, and Fund Administrators.

Role Overview

We are seeking a dedicated and detail-oriented Data Analyst - Private Equity to join our Data Engineering team. This role is pivotal in maintaining the integrity and accuracy of our data, particularly in the private equity domain. The successful candidate will ensure that our financial data is complete, consistent, and aligned across various databases and applications. You will work closely with data engineers, QA, product teams, and software engineers to uphold data quality standards and support accurate financial reporting.

Key Responsibilities

1. Financial Data Preparation & Analysis:
   • Verify and maintain the consistency of accounting calculations across all applications, with a focus on private equity data.
   • Develop and implement financial models for complex financial calculations to ensure they are accurate and reliable.
   • Perform thorough checks to ensure that data in applications reflects real-world private equity scenarios and transactions.
2. Data Testing & Verification:
   • Develop, support and maintain data quality testing frameworks to validate business logic against private equity standards.
   • Collaborate with data engineers to create and manage synthetic data sets for testing edge cases and complex private equity scenarios.
   • Conduct rigorous testing of data pipelines, ensuring all transformations and calculations are performed correctly.
3. Issue Resolution & Debugging:
   • Critically evaluate the representation of investments and fund data to determine suitability and if not determine feasible steps to a solution.
   • Identify, troubleshoot, and resolve data quality issues, particularly those impacting private equity metrics and financial reporting.
   • Work with software engineering and QA teams to debug and fix data discrepancies and inconsistencies.
4. Collaboration & Communication:
   • Act as a liaison between the data engineering team and other stakeholders, including product, software, QA, and client onboarding teams.
   • Provide subject matter expertise in private equity data requirements.
   • Translate private equity concepts into actionable insights for non-finance teams, enabling stakeholders to make informed product and technical decisions.
5. Client Onboarding Support:
   • Assist the client onboarding team by providing expertise in private equity data standards and requirements.
   • Ensure that new client data is accurately integrated into our systems and meets all necessary quality standards.

Requirements

1. Must-Haves:
   • Experience: Proven experience in private equity or accounting, with a strong understanding of private equity industry practices and standards.
   • Technical Skills: Basic knowledge of SQL / Python (+1 year experience), with a strong willingness to learn and expand data skills. Experience working with large datasets is a plus.
   • Communication: Excellent verbal and written communication skills, with the ability to explain complex financial data concepts to non-technical stakeholders.
   • Detail-Oriented: Strong attention to detail, especially in validating complex financial calculations and data transformations.
2. Nice-to-Haves:
   • Technical Tools: Experience with DBT (Data Build Tool) and Snowflake.
   • Accounting Background: Prior experience in accounting or financial data analysis, with the ability to apply this knowledge to production data pipelines.
   • Data Engineering: Familiarity with data engineering concepts and practices, including data pipelines and ETL processes.

Why Join Us?

• Impactful Work: Play a crucial role in ensuring data integrity for critical private equity operations and reporting.
• Professional Growth: Opportunities to learn and grow in the private equity data analysis space, with access to cutting-edge tools and technologies.
• Collaborative Environment: Work alongside a diverse team of data engineers, QA, product managers, and software engineers, contributing to a high-impact project.