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Remote Data Extraction Jobs in Utah (NOW HIRING)

United States (Remote) Travel: Requires domestic travel up to 25% of the time What You'll Be Doing ... Data enrichment - Being able to find, understand and extract data in order to drive successful ...

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Remote Data Extraction information

What are the key skills and qualifications needed to thrive as a Remote Data Extraction Specialist, and why are they important?

To thrive as a Remote Data Extraction Specialist, you need proficiency in data analysis, attention to detail, and experience with data extraction and transformation techniques, often supported by a degree in computer science, information systems, or a related field. Familiarity with tools such as SQL, Python, web scraping frameworks (like BeautifulSoup or Scrapy), and data management platforms is typically required. Strong problem-solving skills, self-motivation, and effective communication are valuable soft skills for excelling in a remote environment. These abilities ensure accurate data collection, efficient workflow, and reliable delivery of insights for business or research needs.

What are some common challenges faced in a remote data extraction role and how can they be addressed?

One common challenge in remote data extraction is ensuring data accuracy while working independently, especially when dealing with large and diverse datasets. Discrepancies can arise from inconsistent data formats or sources, so developing strong attention to detail and utilizing reliable extraction tools is critical. Another challenge is communication, as collaborating with data analysts or project managers remotely requires proactive updates and clear documentation. To address these issues, it's helpful to establish regular check-ins with your team, use standardized data templates, and stay organized with project management software.

What is remote data extraction?

Remote data extraction is the process of retrieving and collecting data from various sources—such as websites, databases, or documents—without being physically present at the source location. This is typically achieved using specialized software, scripts, or tools that can access and gather data over the internet or through remote connections. Professionals in this field often automate data collection tasks to save time and improve accuracy, especially when dealing with large volumes of information. Remote data extraction is commonly used for business intelligence, market research, competitive analysis, and data migration projects.

What is the difference between Remote Data Extraction vs Remote Data Entry?

AspectRemote Data ExtractionRemote Data Entry
Primary FocusExtracting data from various sources like websites, PDFs, or imagesInputting data into databases or spreadsheets
Skills RequiredWeb scraping, data analysis, attention to detailTyping speed, accuracy, basic computer skills
Tools UsedWeb scraping software, OCR tools, data management platformsExcel, Google Sheets, data entry software
Work EnvironmentMostly independent, often project-basedConsistent, repetitive tasks

Remote Data Extraction involves retrieving data from various sources, requiring technical skills like web scraping and data analysis. Remote Data Entry focuses on inputting data accurately into systems, emphasizing speed and precision. Both roles are remote-friendly but differ in technical complexity and daily tasks.

What are the most commonly searched types of Data Extraction jobs in Utah? The most popular types of Data Extraction jobs in Utah are:
What cities in Utah are hiring for Remote Data Extraction jobs? Cities in Utah with the most Remote Data Extraction job openings:
Consultant - AI Solutions Architect

Consultant - AI Solutions Architect

Cicero Group

Salt Lake City, UT • On-site, Remote

Full-time

Posted 13 days ago


Job description

About the Role
MGT is hiring AI Solutions Architects to join our AI Operating Group (AI OG). The AI OG is responsible for both internal AI tool development and client-facing AI solution delivery, primarily serving the state and local government market.
This is a hands-on role. You will design and build AI-powered solutions for real client problems, not write slide decks about what AI could do. You will work across the full lifecycle: discovery, architecture, build, deployment, and iteration. The right person for this role sits comfortably at the intersection of technical capability and business problem-solving.
This is not a traditional software engineering position. It is the cross roads of consulting and building. We need people who can sit in a room with a client, understand their operational challenge, and translate that into a working AI architecture. You should be comfortable with concepts like RAG pipelines, agentic workflows, prompt engineering, and cloud deployment. But your real value is in how you think and solve problems, not just what you can code.
What You'll Do
• Design end-to-end AI solution architectures for client engagements, from problem discovery through production deployment
• Build and implement RAG pipelines, agentic workflows, and multi-agent systems using frameworks such as LangChain and LangGraph
• Architect data pipelines and integration patterns that connect AI capabilities to existing client systems and data sources
• Work with tool-layer integration standards such as MCP (Model Context Protocol) to connect agents with enterprise systems
• Develop reusable components, skills, templates, and accelerators that scale across multiple engagements
• Collaborate with project leads, consultants, and subject matter experts to translate business requirements into technical specifications and solution designs
• Support internal product development across MGT's AI tool suite
• Present technical architectures and solution recommendations to both internal leadership and client stakeholders
• Participate in discovery sessions and workshops to identify high-impact AI use cases within client organizations
Required Qualifications
• 3-5 years of professional experience; does not have to be in AI, but must demonstrate strong technical problem-solving ability and a track record of building solutions that work
• Hands-on experience with one or more of the following: LLM-based application development, retrieval-augmented generation (RAG) architectures, agentic design patterns, prompt engineering, or vector databases
• Demonstrated ability to learn new technical capabilities and platforms quickly
• Strong communication skills; you will work with consultants, clients, and executive leadership, not just engineers
• Ability to independently scope, architect, and deliver technical solutions with minimal oversight
• A builder mentality: you would rather figure it out and ship it than wait for a detailed specification
• Bachelor's degree or equivalent practical experience
Preferred Qualifications
• Experience in consulting, professional services, or client-facing technical delivery
• Background in data architecture, ETL/ELT pipelines, or analytics platforms
• Programming experience in Python or similar languages
• Experience working with cloud-based AI services on any major platform
What Success Looks Like
• Within 30 days: You understand our current tool suite, architecture patterns, and active client engagements. You have shipped something.
• Within 90 days: You are independently architecting solutions for client projects and contributing to internal product development.
• Within 6 months: You are leading technical delivery on engagements, mentoring team members on AI solution patterns, and shaping our approach to new use cases.
Why MGT
You will be joining a team that is actively building and shipping AI products, not talking about them. We have real tools in production, real clients using them, and a leadership team that understands both the technology and the business.
This is a high-visibility role with direct access to senior leadership and the opportunity to shape how AI gets delivered across the organization. We are building the AI practice from the ground up, which means you will have an outsized impact on the tools, processes, and culture of the team.
Our philosophy: clean data foundations first, AI layered on top. Process understanding before automation. Empowering domain experts to build, not centralizing AI capability in a silo. If that resonates with you, this is your team.
NOTE: We currently do not accept candidates who require sponsorship, nor are we able to provide sponsorship opportunities to candidates.
Positions are available in Salt Lake City, Utah; Washington, D.C.; and remote. Remote employees will be expected to travel to an office periodically.