Data Operations Specialist
About The Position
We are seeking a detail-oriented Data Operations Specialist to join our team at Brilliant Harvest. This role is central to transforming documents and raw data into structured, meaningful, and usable information. By adding context, verification, and precision, you will ensure the quality and reliability of our data assets, supporting downstream processes and analytics. In addition to annotation work, this role will also support coordination with third-party annotation partners and contribute to operational processes that ensure efficient, scalable data workflows.
Requirements
- Strong attention to detail and commitment to accuracy.
- Ability to follow structured guidelines and apply them consistently.
- Familiarity with digital documents, data management, or information processing.
- Strong written communication skills.
- Comfortable working independently in a remote environment.
- Experience with annotation, labeling, or metadata tools is an asset and training will be provided.
- Basic project management or task coordination experience.
- Experience working with third-party vendors or distributed teams.
- Familiarity with project tracking tools (e.g., spreadsheets, task management platforms).
- Ability to manage multiple priorities and deadlines in a fast-paced environment.
Nice To Haves
- Understanding of heavy equipment in agriculture or construction
- Experience supporting data operations, annotation workflows, or AI/ML data pipelines
- Strong organizational skills with a process-oriented mindset
Responsibilities
- Data Labeling: Tag and annotate documents, objects, and text (e.g., highlighting key information in equipment service manuals, identifying entities, or marking relevant sections).
- Metadata Creation: Assign categories, keywords, and structured data to improve searchability, consistency, and usability.
- Quality Control: Verify labels, annotations, and metadata against established standards and guidelines.
- Contextual Notes: Add explanations, highlights, or corrections to improve clarity and accuracy.
- Pattern Identification: Detect anomalies, errors, or unique features within datasets and flag them appropriately.
- Third-Party Vendor Management: Work closely with external annotation partners to communicate requirements, provide clarifications, and ensure alignment with internal standards.
- Task Prioritization & Tracking:Help manage annotation queues, assign work (internally or externally), and track progress against deadlines.
- Feedback & Iteration Loops: Review vendor outputs, provide structured feedback, and collaborate to continuously improve quality and efficiency.
- Process Documentation:Help define, document, and refine annotation guidelines, workflows, and standard operating procedures.
- Workflow Optimization:Identify inefficiencies in annotation or data processing workflows and recommend improvements.
- Reporting & Metrics:Track key metrics (quality, throughput, turnaround time) and provide updates to stakeholders.
Benefits
- Join a proven team led by serial entrepreneur, Remi Schmaltz that has successfully exited 2 previous agriculture companies.
- Remote-first role with flexible work environment.
- Opportunity to contribute to meaningful projects in the growing field of data and information management.
- The opportunity to contribute to an innovative product team shaping the future of AI used in the large equipment space.
- A collaborative culture that values growth, learning, and impact.
- Competitive compensation, ESOP and benefits.
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What This Job Offers
Job Type
Full-time
Career Level
Entry Level
Education Level
No Education Listed
Number of Employees
11-50 employees
