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Compensation Data Analyst

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Overview

Schedule
Full-time
Career level
Senior-level
Remote
On-site
Benefits
Career Development

Job Description

About Compa

Compa is a venture-backed AI startup revolutionizing the future of compensation.

In a dynamic job market with hiring challenges, accountability, and the rise of AI, companies need the best data to stay ahead of industry changes, competition, and costs. Compa has developed the premier real-time compensation data platform, delivering top-tier compensation intelligence to leading enterprise teams.

Compa is a compensation intelligence company built to augment enterprise compensation teams in the era of AI.

Our customers include the world’s biggest companies: NVIDIA, Stripe, DoorDash, Open AI, TMobile, Moderna, Workday, Ulta, Target, and more.

Locations:

Compa headquarters are located in Irvine, California, with growing sites in Denver, Colorado and San Francisco, California. We’re a collaborative, curious, and driven team that values transparency, ownership, and continuous learning and prioritizing in person work where possible.

The Role:

The Compensation Data Analyst plays a critical role in maintaining trust in Compa’s compensation insights by monitoring data yields, identifying systemic data issues, resolving customer-specific data problems, and supporting ongoing data releases and quality management.

Key Responsibilities

  • Monitor the health and recency of compensation data across customer accounts.

  • Investigate and resolve data inconsistencies to ensure reliable insights in the platform.

  • Partner with Product, Engineering, and Integrations teams to support stable data pipelines.

  • Respond to customer- and internally-reported data questions with clear, timely communication.

  • Execute routine data updates and validate accuracy as part of ongoing data releases.

  • Perform recurring data quality checks to proactively maintain data integrity.

  • You’ll work at the intersection of compensation expertise, data operations, and product quality.

  • The role offers clear ownership and visibility, with meaningful impact on customer trust and product reliability.

Minimum Qualifications:

  • Experience working with structured datasets and performing data validation or quality checks.

  • At least 3 years of experience working with compensation data and deep knowledge of compensation benchmarking

  • Familiarity with HR technology systems and comfort working with technology systems.

  • Strong analytical and problem-solving skills with attention to detail.

  • Ability to communicate clearly about data findings and issues with both technical and non-technical stakeholders.

  • Comfort working in a fast-paced, collaborative environment with evolving priorities.

Preferred Qualifications:

  • Exposure to data integrations or APIs.

  • Data analysis and proficiency in advanced data analysis (SQL, Python, etc.)

  • Prior experience in a customer-impacting or support-adjacent role, where clear communication and timely resolution were important.

Automate your job search with Sonara.

Submit 10x as many applications with less effort than one manual application.

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FAQs About Compensation Data Analyst Jobs at Compa

What is the work location for this position at Compa?
This job at Compa is located in Irvine, California, according to the details provided by the employer. Some roles may also include multiple work locations depending on the requirement.
What pay range can candidates expect for this role at Compa?
Employer has not shared pay details for this role.
What employment applies to this position at Compa?
Compa lists this role as a Full-time position.
What experience level is required for this role at Compa?
Compa is looking for a candidate with "Senior-level" experience level.
What is the process to apply for this position at Compa?
You can apply for this role at Compa either through Sonara's automated application system, which helps you submit applications 10X faster with minimal effort, or by applying manually using the direct link on the job page.