Full-Time

Data Operations Lead

Confirmed live in the last 24 hours

Old Well Labs

Old Well Labs

1-10 employees

Data platform for fund manager research

Data & Analytics
Fintech
Financial Services

Mid

Charlotte, NC, USA

Category
Data Management
Data & Analytics
Required Skills
SQL
Postgres
JIRA
SCRUM
Confluence
Requirements
  • 4+ years experience in data operations or project management with a strong data focus.
  • Experience supporting a B2B SaaS product.
  • Participating and managing processes like kanban or scrum using tools like Jira.
  • Strong documentation skills (e.g., requirements, test scripts, project status, management presentations, etc.) using tools like Confluence.
  • Experience with relational databases (postgres a plus), Basic/Intermediate SQL (reading, writing a plus) and data modeling (consuming, designing a plus).
  • Experience with ETL processes, either completely bespoke or vendors.
  • Experience with reporting and data quality measurement.
  • Enjoy building process and building out details from ambiguity.
Responsibilities
  • Execute manual processes for loading, manipulating and verifying data quality.
  • Manage teams executing manual data processes and verify quality.
  • Verifying data quality of production data.
  • Own documentation of our data processes.
  • Evolve our data processes to deal with engineer changes, product changes and scale.
  • Collaborate with engineering team to understand changes in the data pipelines and provide feedback.
  • Collaborate with product team to understand how to improve processes and data quality to improve the end user product.

Old Well Labs provides a data platform tailored for the financial technology sector, aimed at helping allocators connect with and monitor fund managers worldwide. The platform is designed for institutional investors such as endowment funds, hedge funds, venture capital, private equity, and real estate investors. It operates on a subscription model, granting users access to a vast database containing over 1 billion data points related to fund managers, including information on portfolio changes, team changes, and price movements. Originally created as an internal tool for an investment firm, the platform has expanded to meet the market's demand for a centralized solution for fund manager research. Old Well Labs differentiates itself by offering a comprehensive and efficient resource that enhances decision-making for its clients, ultimately saving them time in their investment research efforts.

Company Stage

Series A

Total Funding

N/A

Headquarters

Charlotte, North Carolina

Founded

N/A

Growth & Insights
Headcount

6 month growth

50%

1 year growth

50%

2 year growth

50%
Simplify Jobs

Simplify's Take

What believers are saying

  • The recent Series A funding led by Nellore Capital indicates strong investor confidence and provides resources for further development and expansion.
  • OWL's subscription-based model ensures a steady revenue stream, allowing for continuous platform enhancements and customer support.
  • The platform's ability to save time and enhance decision-making for institutional investors makes it an attractive tool in the competitive financial technology sector.

What critics are saying

  • The financial technology sector is highly competitive, with numerous players offering similar data services, which could pressure OWL to continuously innovate.
  • Reliance on subscription fees means that any downturn in client acquisition or retention could significantly impact revenue.

What makes Old Well Labs unique

  • Old Well Labs offers a unique centralized data platform specifically tailored for institutional investors, setting it apart from more generalized financial data services.
  • The platform's origin as an internal tool for an investment firm gives it a practical edge, having been refined through real-world application before market release.
  • With over 1 billion data points, OWL provides an unparalleled depth of information on fund managers, portfolio changes, and market movements.

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