Data and Reporting Analyst at Toptal
We created Toptal to solve an extremely difficult, real-world problem: the talent shortage.
Learn more about us and how to join our core team today.

Job Description

About Toptal

Toptal is a global network of top talent in business, design, and technology that enables companies to scale their teams, on-demand. With $200+ million in annual revenue and over 40% year-over-year growth, Toptal is the largest fully distributed workforce in the world.

We take the best elements of virtual teams and combine them with a support structure that encourages innovation, social interaction, and fun (see this video from The Huffington Post). We see no borders, move at a fast pace, and are never afraid to break the mold.

Position Description

As a Data and Reporting Analyst and subject matter expert (SME) to Talent Operations, you will play a critical role in providing analytics and insights that will contribute to the identification of process improvements and the efficiency and effectiveness of operations. Toptal’s Data and Reporting Analysts are the experts that develop, enhance, and validate performance reporting. You will be a critical part of Toptal’s Data solution, supporting data end-users throughout the company by specializing in a complex and high impact operational area. Your views, analyses, and dashboards will support decisions made by process architects, decision makers, and leadership throughout Toptal.

While this role interfaces, collaborates, and validates work with other analysts across the company, it serves as a dedicated SME for the data collected as a result of our talent acquisition, talent screening, and talent/client matching processes under Talent Operations.

This is a remote position that can be done from anywhere. All communication and resumes must be submitted in English. We are unable to provide visa sponsorship at this time.


Your ability to build products that accurately represent data generated by Talent Operations, and Toptal as a whole, will help facilitate decision-making processes across the entire organization. You will partner with developers, product managers, and other stakeholders to showcase identified issues and recommend solutions targeting the root cause.

In your role, you will create dashboards, metrics/KPIs, reports, and data dictionaries that act as sources of truth to our end users with a high degree of reliability and precision. Your work will have visibility throughout the company, and you will interact and communicate with executives and team leads to ensure that Toptal’s operations are guided by data.

In this role, you will be part of a team executing upon an operating framework and strategy for data and analytics at Toptal. You will collaborate with other analysts to validate and ensure the quality of work products. Being the Talent Operations SME, you will assist our Data Engineers, Data Scientists, and other Business Analysts with work products that require your institutional knowledge. You will recommend data warehousing and ETL strategies that are optimized for the end users.

In the first week you will:

  • Onboard and integrate into Toptal.
  • Rapidly begin learning about Toptal’s history, culture, and vision, with a heavy focus on how verticals operate at Toptal.
  • Shadow key teams across the company to learn the core of Toptal’s operations and capabilities, including SMB, Enterprise, and Talent Operations.

In the first month you will:

  • Review and document the current state of views, dashboards, data dictionaries, and supporting material throughout Toptal.
  • Understand the data generated through company operations and activities.
  • Cross-train with other Business Analysts across the organization.

In the first three months you will:

  • Develop a complete analysis of the screening funnel and related processes.
  • Validate current cross-functional and full-funnel dashboards.
  • Contribute to the standardization of data work products.

In the first six months you will:

  • Develop data dictionaries for the measures and data points that are unique to Talent Operations.
  • Develop a complete analysis of the sourcing funnel and related processes.
  • Partner with the Director of Business Analytics and other analysts to develop and execute upon a standardized analytics framework.

In the first year you will:

  • Monitor adherence to the new analytics framework discipline within Talent Operations.
  • Propose new data-driven solutions and strategies to teams and individuals within Talent Operations.


  • At least 3 years of Data/Analytics work experience.
  • Ability to learn business processes at a near-native level to understand the role that analytics plays in supporting the business.
  • Track record of tying analytics to recommendations that result in improved business processes.
  • Demonstrated data visualization and querying (SQL) expertise. Tableau experience is preferred, but similar systems with transferable skill-sets (Looker, QlikView, Periscope, PowerBI, etc.) are acceptable.
  • Ability to consult and collaborate with data scientists and machine learning experts. Working knowledge of probability and statistics is required; experience in programming languages used in data science (R, MATLAB, Python) is a plus.
  • Exceptional written and verbal communication skills, including the ability to avoid complexity and create simplified and intuitive recommendations at an executive level.
  • Strong professional skepticism, including the ability to challenge assumptions/calculations, communicate limitations, and flag blind spots.
  • Ownership of assigned tasks and duties, taking responsibility for the quality, accuracy, and timeliness of data products.
  • Self-motivated, able to be hands-on when analyzing, interpreting, and deriving insights into business reports, analytic models, and data sources.
  • Strong attention to detail.
  • You must be a world-class individual contributor to thrive at Toptal.
For Toptal Use Only: #south #individualcontributorSA #southamerica
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Required skills


North and South America


Full Time

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