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Entry Level Data Extraction Jobs in New York (NOW HIRING)

GainAm

Entry Level Data Analyst job

Hicksville, NY · On-site

$70K/yr

... extract the data needed Removing corrupted data and Performing initial analysis to assess the quality of the data Performing further analysis to determine the meaning of the data Performing final ...

United Airlines

JR Data Analyst

Manhattan, NY · On-site

We are looking for a motivated entry-level professional with a strong foundation in Computer ... Write and optimize SQL queries for data extraction and manipulation. * Support the development and ...

MedReview

ETL Engineer

New York, NY · On-site

$120/hr

This is not an entry-level role. You will be working with modern data tools and large datasets ... Design and develop ETL pipelines using SSIS, Azure Data Factory, and Databricks * Build and ...

MedReview

ETL Engineer

Manhattan, NY · On-site

This is not an entry-level role. You will be working with modern data tools and large datasets ... Design and develop ETL pipelines using SSIS, Azure Data Factory, and Databricks * Build and ...

ADG555

Entry Level Business Analyst

Glen Rock, NJ

... extract data from a database. - Excellent verbal and written communication skills, including experience working directly with customers to discuss their requirements and objectives. Additional ...

ADG555

Entry Level Business Analyst

Glen Rock, NJ · On-site

... extract data from a database. - Excellent verbal and written communication skills, including experience working directly with customers to discuss their requirements and objectives. Additional ...

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Entry Level Data Extraction information

What are some common challenges faced in an entry level data extraction role, and how can they be addressed?

Entry level data extraction professionals often encounter challenges such as dealing with inconsistent data formats, handling large volumes of unstructured information, and learning new data extraction tools or software. Addressing these challenges involves developing strong attention to detail, collaborating closely with team members to share best practices, and proactively seeking training opportunities to build technical skills. Regular communication with supervisors and peers can also help in troubleshooting issues and improving workflow efficiency.

What is the difference between Entry Level Data Extraction vs Data Analyst?

AspectEntry Level Data ExtractionData Analyst
Required CredentialsHigh school diploma or equivalent; basic knowledge of data toolsBachelor's degree in data science, statistics, or related field
Work EnvironmentData collection, cleaning, and initial processing; often in data-focused teamsData analysis, interpretation, reporting; often in cross-functional teams
Employer & Industry UsageUsed in tech, finance, marketing for data gathering tasksUsed across industries for insights, decision-making, and reporting

Entry Level Data Extraction involves gathering and preparing data for analysis, requiring basic technical skills. Data Analysts build on this foundation, performing in-depth analysis, interpretation, and reporting. While data extraction is a starting point, data analysis involves a broader skill set and strategic insights.

What is an Entry Level Data Extraction job?

An Entry Level Data Extraction job involves collecting, organizing, and processing data from various sources, such as documents, websites, or databases. People in this role typically use basic tools and software to extract relevant information, ensuring its accuracy and completeness. These positions are suitable for individuals new to the field and often require attention to detail, basic computer skills, and sometimes familiarity with data management tools. Entry level data extraction jobs serve as a starting point for careers in data analysis and data management.

What are the key skills and qualifications needed to thrive as an Entry Level Data Extraction specialist, and why are they important?

To thrive as an Entry Level Data Extraction specialist, you need strong attention to detail, basic data analysis skills, and familiarity with spreadsheets or databases, often supported by a high school diploma or equivalent. Commonly used tools include Microsoft Excel, Google Sheets, and sometimes data extraction software or simple scripting languages like Python. Strong organizational skills, problem-solving abilities, and effective communication help you excel in handling large volumes of information and clarifying data requirements. These skills ensure accuracy, efficiency, and reliability in preparing and delivering data critical for business decisions.
What are the most commonly searched types of Data Extraction jobs in New York? The most popular types of Data Extraction jobs in New York are:
What are popular job titles related to Entry Level Data Extraction jobs in New York? For Entry Level Data Extraction jobs in New York, the most frequently searched job titles are:
What job categories do people searching Entry Level Data Extraction jobs in New York look for? The top searched job categories for Entry Level Data Extraction jobs in New York are:
Entry Level Data Extraction jobs near you
Infographic showing various Entry Level Data Extraction job openings in New York as of July 2026, with employment types broken down into 1% As Needed, 80% Full Time, 11% Part Time, and 8% Contract. Highlights an 83% Physical, 3% Hybrid, and 14% Remote job distribution.

Entry Level Data Analyst job

GainAm

Hicksville, NY • On-site

$70K/yr

Full-time

Posted 4 days ago

Job description

Required Skills
A high level of mathematical ability Programming languages, such as SQL, Oracle and/or Python The ability to analyze, model and interpret data Problem-solving skills Capable of Deep Work, Problem Solver, Reliable, consistent, Attention to detail
Required Experience
Ability to learn and utlize Exploratory Data Analysis and Data Cleansing Ability to Write SQL Scripts for Data Warehousing Understanding and knowledge of Ad Hoc Business Analysis
Day to day work involves proficiency in using advanced computerized models to extract the data needed
Removing corrupted data and Performing initial analysis to assess the quality of the data
Performing further analysis to determine the meaning of the data
Performing final analysis to provide additional data screening
Preparing reports based on analysis and presenting to management

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