Data Specialist

Role overview

This is a fully remote opportunity for a Data Specialist in the United States, offered through a partner employer that handles the application review and hiring process. The position centers on end-to-end ownership of data infrastructure, analytics, and reporting in a global setting.

You will help turn raw information into dependable insights by building stable pipelines, creating scalable reporting layers, and protecting the accuracy of key business metrics. The role calls for a high level of independence, careful execution, and a proactive approach to solving problems. Your work will have a direct impact on strategic choices and day-to-day performance across the organization.

Core accountabilities

• Oversee and improve complete data pipelines and warehouse processes using ETL platforms such as Stitch and Google BigQuery.
• Develop, update, and support dashboards and reporting assets in Looker Studio for business intelligence use across teams.
• Set up, validate, and continuously monitor Google Analytics 4 tracking to keep event data and reports consistent.
• Run thorough QA and validation checks to make sure reporting outputs remain accurate, consistent, and dependable.
• Watch data flows actively, spot unusual patterns early, and take corrective steps before issues affect decisions.
• Create custom reports and ad hoc analyses for teams across the business.
• Work with engineering and stakeholders to refine data architecture, tracking, and reporting processes.
• Keep clear documentation, organized task tracking, and structured workflows using tools like Trello and Slack.

Required profile

The role requires at least 3 years of experience in a Data Analyst, Data Specialist, or analytics-oriented position. You should have practical exposure to data pipelines, ETL tools similar to Stitch, and data warehousing in BigQuery.

Strong capability in Looker Studio is important, including dashboard development and advanced calculated metrics or report logic. Experience with GA4 is preferred, especially for event tracking, implementation, and reading behavioral data.

You must be comfortable validating datasets, auditing dashboards, and maintaining end-to-end data quality. The role also calls for strong analytical thinking, the ability to identify trends and anomalies, and confidence in producing insights for cross-functional teams in a fast-paced environment.

Excellent organization, clear documentation habits, independent task management, and strong communication are essential for success in a distributed team setup.

Benefits

• Remote-first setup with flexibility across global time zones.
• A chance to shape data-informed decisions across the business.
• High ownership and autonomy over analytics and data systems.
• Access to modern data stack tools and technologies.
• Fast-moving, low-bureaucracy environment that values execution and impact.
• Strong culture of experimentation and ongoing improvement.
• Collaborative global team environment.
• Opportunity to create scalable analytics systems from the ground up.

Application and hiring process

This listing is handled by a partner company, which manages applications and the next steps after submission. Candidates are reviewed using an AI-assisted matching process, with the strongest matches passed along to the hiring employer. Interviews, assessments, and the final hiring decision are managed internally by the employer.

Data privacy notice

By applying, you agree that the recruitment platform may process your personal information to assess your candidacy and share relevant details with the hiring employer. This processing is carried out under legitimate interest and pre-contractual measures where applicable, including GDPR-based rights such as access, correction, deletion, and objection.

Artificial intelligence tools may be used to support parts of screening, such as reviewing applications, analyzing resumes, or checking for inconsistencies in submitted materials. These tools assist the recruitment team but do not replace human judgment. Final hiring decisions are made by people. If you want more information about how your data is handled, you can contact the team directly.