Data Operations Analyst

At Brightfield, we are revolutionizing the way organizations manage their workforce. As a pioneer in workforce analytics, our AI-powered platform, TDX (Talent Data Exchange), helps the world’s largest companies make smarter decisions about how they design, source, and manage their extended workforce.

With over $573B in real-world workforce spend data from 139 countries, we provide the insights our customers need to reduce costs, manage risk, and unlock new levels of agility and performance. Since 2006, we’ve been trusted by the Global 2000 to guide strategic workforce decisions with clarity and confidence.

We are a fully remote team of data-driven innovators, problem solvers, and industry experts who value flexibility, ownership, and continuous learning. At Brightfield, how we work together matters—and we’re building a company where curious, driven people can do their best work.

Brightfield is seeking a Data Ops Analyst who combines strong analytical thinking with excellent communication skills. This role is ideal for someone who enjoys solving business problems, working directly with customers, and transforming complex data into actionable insights.

The successful candidate will be comfortable working extensively in Excel, analyzing large datasets, managing multiple priorities, and partnering directly with customers to solve business challenges, while automating manual processes. They are naturally curious, strong communicators, and effective problem solvers who can navigate ambiguity, ask thoughtful questions, and ensure business needs are fully understood before developing analytical solutions. This individual combines technical capability with sound judgment, attention to detail, strong organizational skills and a commitment to delivering accurate, high-quality work and exceptional customer experiences.

• Data Analysis and Problem Solving: Analyze workforce and business data to identify trends, patterns, and opportunities; investigate customer questions and business challenges using a structured analytical approach; translate business needs into data-driven solutions and recommendations; identify anomalies, inconsistencies, and potential issues within datasets; support the development of customer deliverables and reporting solutions.
• Customer Partnership and Communication: Work directly with customers to understand business objectives and reporting requirements; participate in customer meetings and presentations; present findings and recommendations in a clear, concise, and actionable manner; ask thoughtful clarifying questions to ensure requirements and expectations are fully understood; provide timely updates on deliverables and project status; build trusted relationships through responsiveness, professionalism, and follow-through.
• Data Quality and Standards: Ensure data accuracy, consistency, and completeness across datasets and deliverables; perform quality assurance reviews of analyses and reports prior to customer delivery; investigate and resolve data discrepancies; maintain organized documentation of methodologies, assumptions, and findings.
• Project and Portfolio Management: Manage multiple projects and customer requests simultaneously; prioritize work effectively in a fast-paced environment; collaborate with Customer Success, Product, and Data teams to support customer initiatives; adapt to changing priorities while maintaining quality and meeting deadlines.
• Business Acumen and Continuous Learning: Develop an understanding of customer needs, business processes, and industry concepts to inform analytical solutions; demonstrate curiosity and a willingness to learn new business concepts, industries, tools, and analytical methodologies; seek and apply…