Key Facts

Remote From:

Fixed term

Mid-level (2-5 years)

English

Hard Skills

Data Quality Assessment Web Crawling Data Architecture Documentation Generation Engineering Documentation Data Processing Web Crawling Project Management Business Intelligence Tools Data Collection Data Architecture Project Coordination Analytics Data Architecture

Other Skills

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Data Reporting
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Quality Assurance
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Non-Verbal Communication
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Integrative Thinking
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Analytical Skills
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Organizational Skills
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Detail Oriented
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Problem Solving

Roles & Responsibilities

2+ years of professional experience in data operations, analytics support, QA, project coordination, or similar operational roles.
Familiarity with data pipelines, scraping workflows, or data QA processes.
Strong attention to detail and ability to identify inconsistencies in datasets and operational workflows; excellent organizational and project management skills.
Strong written and verbal communication skills in English; ability to work independently and proactively follow issues through to resolution; comfortable with datasets, reporting tools, and structured documentation.

Requirements:

Monitor ongoing government website scraping pipelines to ensure data is collected accurately and consistently; track pipeline health and identify issues affecting scraping reliability.
Perform regular QA checks on datasets and scraped data to identify broken links, structural changes, or inconsistencies; flag issues to engineering quickly.
Create and maintain evaluation benchmarks to assess scraping performance, dataset completeness, and pipeline reliability.
Manage project tracking across scraping initiatives, ensuring tasks, timelines, and deliverables are clearly organized and executed; coordinate issue reporting and process improvements with engineering.

Job description

This role is open to candidates based in LATAM, Africa, and Eastern Europe. Please note that as this role supports U.S.-based clients, candidates must be available to work during U.S. business hours aligned with the client’s time zone.

Our client is an innovative technology company that uses AI to help organizations make better decisions through data insights and advanced analytics. Their platform aggregates and analyzes large datasets from public and government sources, transforming complex information into actionable intelligence for businesses and institutions.

Location

Fully Remote (Work from Home) | 7 AM – 3 PM EST (Flexible)

Role Overview

The Data Operations Specialist will support the ongoing monitoring and quality assurance of large-scale data pipelines that rely on government website scraping. This role focuses on ensuring data collection systems remain accurate and reliable as external websites change, URLs break, or site structures shift. The position is highly operational, requiring strong attention to detail, organized task management, and proactive coordination with engineering teams to maintain transparency and consistency across multiple scraping projects.

Key Responsibilities

Data Pipeline Monitoring

Monitor ongoing government website scraping pipelines to ensure data is collected accurately and consistently.
Track pipeline health and identify issues affecting scraping reliability.

Quality Assurance & Website Monitoring

Perform regular QA checks on datasets and scraped data to identify broken links, structural changes, or inconsistencies in data collection.
Track changes across government websites that may impact scraping pipelines and quickly flag issues to the engineering team.

Benchmarking & Evaluation

Create and maintain evaluation benchmarks to assess scraping performance, dataset completeness, and pipeline reliability.

Data Analysis & Reporting

Analyze datasets and generate reports to track scraping progress and highlight anomalies or operational issues.
Maintain clear documentation and reporting systems that provide visibility into pipeline health and project progress.

Project & Task Management

Manage project tracking across scraping initiatives, ensuring tasks, timelines, and deliverables are clearly organized and executed.

Issue Coordination & Process Improvement

Communicate effectively with the engineering team when technical issues arise, ensuring problems are documented and resolved quickly.
Identify opportunities to improve monitoring, documentation, and operational processes for data pipelines.

Qualifications

Experience

2+ years of professional experience in data operations, analytics support, QA, project coordination, or similar operational roles.
Familiarity with data pipelines, scraping workflows, or data QA processes is highly advantageous.

Skills

Strong attention to detail and the ability to identify inconsistencies in datasets and operational workflows.
Excellent organizational and project management skills for tracking tasks, deliverables, and timelines across multiple projects.
Strong written and verbal communication skills in English.
Ability to work independently and proactively follow issues through to resolution.
Comfort working with datasets, reporting tools, and structured documentation.
Basic analytical skills for evaluating datasets and identifying potential data issues.
Conscientious and methodical mindset with strong ownership over operational processes.

What Success Looks Like

Scraping pipelines remain well monitored, organized, and reliable, with issues flagged quickly and resolved efficiently.
Data quality remains consistently high through ongoing QA checks and benchmarking.
Pipeline tracking and reporting provide clear visibility into project progress and operational health.
Engineering teams receive clear, well-documented issue reports that accelerate troubleshooting.
Project timelines and deliverables stay on track across scraping initiatives.
Operational workflows remain structured and transparent, improving efficiency across data collection processes.

Opportunity

This role offers the opportunity to join a fast-growing AI-driven technology company working at the intersection of data infrastructure, analytics, and public data intelligence. The Data Operations Specialist will have direct impact on the reliability of critical data systems while gaining exposure to large-scale operational workflows, engineering collaboration, and process improvement in a highly data-focused environment.