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Remote Data Extraction Jobs in Connecticut (NOW HIRING)

Apex Systems

Data Analyst III

Stamford, CT · Remote

$45 - $55/hr

Stamford, Connecticut (Partial Remote) Employment Type: Contract Role Overview This position ... Extract and analyze data from diverse sources such as databases, manual files, and external ...

The Hartford

Data Scientist

Hartford, CT · On-site +1

$90K - $135K/yr

This role can have a Hybrid or Remote work arrangement depending on experience and skillset ... Experience in SQL and navigating databases to extract relevant attributes * Experience in Unix, Git ...

SysMind Tech

IDMC Data Lineage Developer

Stamford, CT · On-site +1

$65 - $75/hr

Thomas Hodges Targeted Bill Rate- $65-$75hr REQUIREMENT_CITY - c/Remote REQUIREMENT_ID-10631715 ... g., databases, ETL, cloud, BI tools). Collaborate with Data Governance, Data Engineering, and ...

pitneybowes

RevOps Analytics Manager

Shelton, CT · On-site +1

$100K - $120K/yr

At least four years of advanced SQL experience for data extraction, transformation, and modeling ... Can be either fully remote (anywhere in U.S.) or hybrid model, depending on proximity to Shelton ...

Ztek Consulting

Dataiku Developer

Stamford, CT · Remote

$100K - $130K/yr

Stamford, CT/ Remote Salary Range : $100,000-$130,000 a year 8 - 12 years of experience Desired ... Solid understanding of ETL/ELT, data modeling, and SQL. * Hands-on expertise with the Azure data ...

The Hartford

AVP Applied AI, Small Business

Hartford, CT · On-site +1

This role can have a Hybrid or Remote work schedule. Candidates who live near one of our office ... data and retrieval approaches, including document ingestion pipelines, OCR, layoutaware extraction ...

ggi

Commercial Analytics Senior Manager

Brookfield, CT · Remote

Remote About the Role: Greenfield is looking for a Commercial Analytics Senior Manager to join our ... Skilled in building semantic models, data models, and ETL/ELT pipelines at scale. * Proficient in ...

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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, 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 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 popular job titles related to Remote Data Extraction jobs in Connecticut? For Remote Data Extraction jobs in Connecticut, the most frequently searched job titles are:
What job categories do people searching Remote Data Extraction jobs in Connecticut look for? The top searched job categories for Remote Data Extraction jobs in Connecticut are:
What cities in Connecticut are hiring for Remote Data Extraction jobs? Cities in Connecticut with the most Remote Data Extraction job openings:
Remote Data Extraction jobs near you

MongoDB Data Engineer - W2 - Hartford, CT/ Remote - Long term Contract

TechVirtue LLC

East Hartford, CT • Remote

$113K - $136K/yr

Other

Posted 3 days ago

Job description

Job Title: MongoDB Data Engineer
Location: REMOTE
Duration: Long Term
Job Description:


MongoDB Data Engineer to design, develop, and maintain scalable data solutions. In this role, you will build efficient data models, implement ETL pipelines, and optimize database performance through indexing, sharding, and schema design best practices. You will work closely with application developers, data analysts, and DevOps teams to ensure data reliability, security, and high availability across environments. The ideal candidate has strong experience with MongoDB, programming skills in Python, and hands-on knowledge of cloud platforms such as Google Cloud Platform, along with expertise in data integration and automation tools.

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