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Temporary Data Extraction Jobs in Arizona (NOW HIRING)

Sonsoft Inc

Informatica and Teradata

Phoenix, AZ · On-site

$52.75 - $69.50/hr

... Design, ETL flow, advanced SQLs * Knowledge of data loading techniques using Informatica tool ... Efficient usage of Teradata DDL Statements - Derived Tables, Volatile Tables and Global Temporary ...

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Temporary Data Extraction information

What is the difference between Temporary Data Extraction vs Data Analyst?

AspectTemporary Data ExtractionData Analyst
Required CredentialsBasic technical skills, often no formal degree requiredBachelor's degree in data-related fields, certifications preferred
Work EnvironmentProject-based, short-term assignments, often remote or on-siteOngoing, full-time or part-time roles within organizations
Industry UsageCommon in data collection, research, and initial data processingUsed for interpreting data, creating reports, and strategic analysis

Temporary Data Extraction involves short-term tasks focused on collecting and extracting data, often requiring basic technical skills. Data Analysts typically hold formal education and perform ongoing analysis to support business decisions. While both roles work with data, their scope, credentials, and work environment differ significantly.

What are Temporary Data Extraction jobs?

Temporary Data Extraction jobs involve short-term assignments where individuals are responsible for collecting, retrieving, and organizing data from various sources, such as documents, databases, or websites. These roles are typically project-based and may require the use of specialized software or tools to extract data efficiently and accurately. Temporary data extraction positions are common in industries undergoing digital transformation, data migration, or large-scale information updates. Workers in these roles need strong attention to detail and may work independently or as part of a team. Since these jobs are temporary, assignments can range from a few days to several months, depending on the project's scope.

What are the typical challenges faced in a Temporary Data Extraction role, and how can they be managed?

Temporary Data Extraction professionals often encounter challenges such as inconsistencies in source data, tight deadlines, and adapting quickly to new tools or procedures. It's important to pay close attention to detail and communicate regularly with team members or supervisors to clarify requirements and resolve ambiguities. Familiarizing yourself with the data extraction software and maintaining organized records can help manage workload efficiently. Additionally, being proactive about asking questions when encountering unclear data can prevent errors and streamline the extraction process.

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

To thrive as a Temporary Data Extraction Specialist, you need strong attention to detail, data entry accuracy, and familiarity with spreadsheets or databases, typically supported by a high school diploma or equivalent. Proficiency with tools such as Microsoft Excel, data extraction software, and sometimes OCR systems is usually required. Analytical thinking, time management, and reliability are crucial soft skills for managing repetitive tasks and meeting deadlines. These competencies ensure accurate data collection, minimize errors, and help maintain workflow efficiency during short-term projects.
What are the most commonly searched types of Data Extraction jobs in Arizona? The most popular types of Data Extraction jobs in Arizona are:
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Temporary Data Extraction jobs near you
Research Data Support Specialist II, Lunar and Planetary Laboratory (Temporary) (Part-Time)

Research Data Support Specialist II, Lunar and Planetary Laboratory (Temporary) (Part-Time)

University of Arizona

Tucson, AZ

Other

Posted 12 days ago

University Of Arizona rating

7.2

Company rating: 7.2 out of 10

Based on 67 frontline employees who took The Breakroom Quiz

343rd of 553 rated colleges and universities

Job description

  • Conduct literature searches and prepare summaries of scientific publications utilizing 50 papers in an Overleaf document, highlighting methodologies, datasets, and findings for review by the principal investigator.
  • Familiarize yourself with Boyle's catalogue.
  • Develop and maintain Python scripts to load, organize, query, and extract data from astronomical catalogs, including the identification of subsets based on established selection criteria (e.g., stellar rotation and effective temperature).
  • Apply stellar rotation-age relationships designated by the project lead from the scientific literature and implement approved methodologies for age estimation (these can be stellar temperature-dependent), including the application of documented uncertainty calculations.
  • Generate data products, statistical summaries, tables, and figures to characterize young 100-500 Myr samples within specified age ranges and support comparisons between GBTDS and TESS datasets.
  • Document findings and present results to research personnel for evaluation and interpretation.
  • Collaborate with other researchers on the team and present at team meetings.

Knowledge,Skills, and Abilities (KSAs):

  • Python proficiency: Demonstrated proficiency in using Python for scientific computing, astrophysical data analysis, and the development of reproducible, research-grade workflows for large astronomical datasets (e.g., time-series or survey data).
  • Attention to detail: Strong ability to ensure scientific accuracy and quality control, including the reliability, traceability, and validation of results derived from complex datasets and research workflows.
  • Communication skills: Ability to clearly communicate technical and scientific information both verbally and in writing, including the documentation of analysis methods and results, and collaboration within multidisciplinary research teams supporting space- and mission-based science.

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