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Remote Data Extraction Jobs in Seattle, WA (NOW HIRING)

This position is available as a hybrid or remote work schedule. Essential Duties, Responsibilities ... DataWarehousing experience - ETL & ELT * PowerBI, Data Analysis Expressions (DAX) * Excel ...

... remote and underserved areas. This role will focus on consumer metrics and insights, conducting ... Experience with ETL processes, data pipelines, or automation scripting (e.g., Python, VBA)

Director, Software Engineering

Seattle, WA · On-site +1

$202K - $299K/yr

With intelligent agreement management, Docusign unleashes business-critical data that is trapped ... Employee divides their time between in-office and remote work. Access to an office location is ...

Solutions Analyst Truveta is the world's first health provider led data platform with a vision of ... Write regex queries using Databricks SQL to extract clinical concepts from clinical notes per ...

Software Engineer Principal

Home, WA · On-site +1

$91K - $202K/yr

Strong experience with REST, SOAP, ETL processes, data movement, and system interoperability ... This position may be eligible for remote work in select geographic locations, subject to approval ...

Showing results 41-51

Remote Data Extraction information

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 are the key skills and qualifications needed to thrive as a remote data extraction specialist?

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 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 Seattle, WA? The most popular types of Data Extraction jobs in Seattle, WA are:
What are popular job titles related to Remote Data Extraction jobs in Seattle, WA? For Remote Data Extraction jobs in Seattle, WA, the most frequently searched job titles are:
What job categories do people searching Remote Data Extraction jobs in Seattle, WA look for? The top searched job categories for Remote Data Extraction jobs in Seattle, WA are:
Infographic showing various Remote Data Extraction job openings in Seattle, WA as of July 2026, with employment types broken down into 1% As Needed, 82% Full Time, 12% Part Time, 1% Temporary, and 4% Contract. Highlights an 88% Physical, 3% Hybrid, and 9% Remote job distribution.

Innovations and AI Solutions Engineer

Wsgr

Seattle, WA • On-site, Remote

Full-time

Re-posted 19 days ago


Job description

Wilson Sonsini is the premier legal advisor to technology, life sciences, and other growth enterprises worldwide. We represent companies at every stage of development, from entrepreneurial start-ups to multibillion-dollar global corporations, as well as the venture firms, private equity firms, and investment banks that finance and advise them. The firm has approximately 1,100 attorneys in 17 offices: 13 in the U.S., two in China, and two in Europe. Our broad spectrum of practices and entrepreneurial spirit allow exceptional opportunities for professional achievement and career growth.

The Innovation and AI Solutions Engineer position is part of the firm's Innovation Department.This position will be responsible for developing, optimizing and growing the firm's corpus of innovation and AI solutions for both practice and enterprise side use cases, as well as optimizing data collection and flows across these solutions.The role will support our attorneys and staff with software development, low/no-code solutions, and data initiatives. The Innovation and AI Solutions Engineer is a self-directed, people-oriented employee who is comfortable supporting the development and data needs of the organization, including clients, attorneys, practice groups and administrative teams.

This position is available as a hybrid or remote work schedule.

Essential Duties, Responsibilities

  • Support innovation projects by facilitating and participating in discussions, meetings with management and department groups, developing business processes, implementing data integrations and recommending best practices on the effective use of data and data analytics tools.

  • Build and maintain innovation and AI solutions alongside optimal data API and pipeline architectures.

  • Design, build and implement machine learning models, including the development of AI Models and prompts for various applications.

  • Collaborate with business users and technical teams to support and improve how data is collected, analyzed and reported throughout the organization.

  • Analyze users needs to determine business and data requirements, effectively applying technology to meet the firm's strategic objectives.

  • Assemble and manage large, complex data sets that meet business and technical requirements.

  • Identify, design, and implement internal process improvements: automating manual processes, optimizing data delivery, and improving infrastructure within assigned projects and data systems.

  • Build system infrastructure and processes for the efficient extraction, transformation, loading and integration of data to and from a wide variety of data sources using SQL, Power BI and Azure technologies.

  • Develop and/or apply analytics tools that utilize data pipelines to provide actionable insights into customer acquisition, operational efficiency, billing analytics, case outcomes, and other key business and legal practice performance metrics.

  • Ensure firm and client data security across multiple office locations, data centers, vendors and applications.

  • Develop data visualization and reporting tools to effectively convey meaningful insights from complex and diverse data sets.

  • Leverage statistics and computational techniques in problem solving.

  • Be familiar with common NLP and machine learning techniques.

  • Research and use applicable models in creative problem solving.

  • Work with GitHub and software version control.

  • Demonstrate the ability to efficiently and smartly document code and end-to-end processes.

  • Implement models in a production environment via custom API's and enterprise solutions. such as Azure.

Experience, Knowledge and Abilities

  • Extensive experience and working knowledge with SQL and relational databases, including query authoring, database management, and creating/maintaining large data stores in SQL and cloud platforms such as Azure or AWS.

  • Experience building and optimizing API's and data pipelines, architectures and data sets.

  • Strong analytic skills related to working with structured and unstructured datasets.

  • Ability to learn new tools and coding languages where required.

  • Ability to organize tasks and priorities under minimal supervision.

  • Experience performing root cause analysis on internal and external data, data integrations and processes to solve specific business problems and identify opportunities for improvement.

  • Experience developing processes that support data transformation, integrations, data structures, metadata, dependency and workflow management.

  • A successful history of manipulating, processing and extracting value from large, disconnected datasets.

  • Experience collaborating with cross-functional teams and stakeholders in a dynamic environment.

  • Ability to handle sensitive and confidential information responsibly.

  • Experience with AI/ML data preparation including feature engineering, data preprocessing, and dataset versioning for machine learning workflows.

  • Knowledge of data bias detection and mitigation techniques to ensure AI models are fair and representative across different legal contexts.

  • Experience with vector databases and embeddings for semantic search and retrieval-augmented generation (RAG) applications.

Technological Proficiency

  • Expertise in applying the following technologies:

    • SQL Server, T-SQL, SSIS & SSRS, Stored Procedures

    • DataWarehousing experience - ETL & ELT

    • PowerBI, Data Analysis Expressions (DAX)

    • Excel / PowerQuery

    • Programming and scripting languages: Python, R, C++, Julia, Javascript, SQL

    • API integration and development tools and scripting

    • Extensive experience working with a variety of data file formats, such as JSON, XML, SQL

  • Additional skills that would be highly advantageous include:

    • PowerShell

    • Regular Expression (Regex)

    • VBA, MS Access & Excel

    • Documentation & Process Mapping

    • Dynamic visualization tools, such as Microsoft Power BI, Tableau, Domo, etc.

    • Experience developing and applying machine learning models using Python, R, SQL and Azure Machine Learning

    • Experience integrating legal industry, line-of-business applications, such as SharePoint, Aderant Financial System, Salesforce.com/CRM, NetDocs/DMS

    • Large Language Model Integration: Experience with OpenAI API, Azure OpenAI, Anthropic Claude, or similar

    • Embedding Models: Familiarity with sentence transformers, OpenAI embeddings, or domain-specific legal embeddings

  • Law firm experience a plus.

Requirements

  • 4+ years of experience in a Data Engineer/DataOps-DevOps role.

  • Bachelor's degree and/or graduate degree in Computer Science, Data Science, Data Analytics, Information Systems or equivalent discipline.

  • Experience with Microsoft SQL Server and related Microsoft data management and integration technologies.

  • Excellent verbal and written communication and interpersonal skills

Preferred

  • AI/ML Data Preparation Certification or equivalent coursework in machine learning data engineering.

  • Experience with legal technology platforms and understanding of legal workflow requirements.

  • Knowledge of data privacy regulations (GDPR, CCPA, HIPAA) as they apply to AI systems in legal contexts.

The primary location for this job posting is in Palo Alto, but other locations may be listed. The actual base pay offered will depend upon a variety of factors, including but not limited to the selected candidate's qualifications, years of relevant experience, level of education, professional certifications and licenses, and work location. The anticipated pay range for this position is as follows:Palo Alto, New York, San Francisco: $116,875 - $158,125 per year. Austin, Boston, Boulder, Century City, Delaware, Los Angeles, Salt Lake City, San Diego, Seattle, Washington, D.C., and all other locations: $105,400 - $142,600 per year.

The compensation for this position may include a discretionary year-end merit bonus based on performance. We offer a highly competitive salary and benefits package.

Benefits information can be found here. Equal Opportunity Employer (EOE).