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Entry Level Data Extraction Jobs (NOW HIRING)

MedReview

ETL Engineer

Manhattan, 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 ...

IDEALFORCE LLC

Data Architect(33397)

Phoenix, AZ

$63.25 - $81.50/hr

... in related roles DW, ETL, BI, or data management - Experience, working knowledge of, or ... entry level to senior leadership Ability to manage multiple projects at the same time and shift ...

IDEALFORCE LLC

Data Developer(33441)

Phoenix, AZ

Develop ETL solutions using SQL Server Integration services (SSIS) Develop reports using SQL Server ... entry level to senior leadership Ability to work on multiple projects at the same time and shift ...

Fuyao Glass America Inc

QC Engineer-Quality

Decatur, IL · On-site

$55K - $63K/yr

This entry-level position is ideal for candidates with a background in business analytics, database ... QUALIFICATIONS / SKILLS: · Experience writing basic SQL queries and performing data extraction · ...

Proctor & Gamble

Data Asset Manager

Box Elder, SD

$85K - $122K/yr

Work with development teams on ETL processes, engage with vendors to integrate governance practices ... Job Schedule Full time Job Number R000147268 Job Segmentation Entry Level Starting Pay / Salary ...

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Entry Level Data Extraction information

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How much do entry level data extraction jobs pay per hour?

As of Jul 9, 2026, the average hourly pay for entry level data extraction in the United States is $20.24, according to ZipRecruiter salary data. Most workers in this role earn between $16.35 and $21.88 per hour, depending on experience, location, and employer.

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.
More about Entry Level Data Extraction jobs
What cities are hiring for Entry Level Data Extraction jobs? Cities with the most Entry Level Data Extraction job openings:
What are the most commonly searched types of Data Extraction jobs? The most popular types of Data Extraction jobs are:
What states have the most Entry Level Data Extraction jobs? States with the most job openings for Entry Level Data Extraction jobs include:
What job categories do people searching Entry Level Data Extraction jobs look for? The top searched job categories for Entry Level Data Extraction jobs are:
Entry Level Data Extraction jobs near you
Infographic showing various Entry Level Data Extraction job openings in the United States as of July 2026, with employment types broken down into 1% As Needed, 84% Full Time, 12% Part Time, and 3% Contract. Highlights an 88% Physical, 2% Hybrid, and 10% Remote job distribution, with an average salary of $42,098 per year, or $20.2 per hour.
Associate Data Engineer - Client Innovation Center (Entry Level)

Associate Data Engineer - Client Innovation Center (Entry Level)

IBM

Lansing, MI • On-site

$14.50 - $19/hr

Full-time

Posted 29 days ago

IBM rating

7.9

Company rating: 7.9 out of 10

Based on 75 frontline employees who took The Breakroom Quiz

105th of 205 rated software companies

Job description

Job Summary:
IBM Consulting Client Innovation Centers (CICs) are environments where technologists build real solutions for clients. The Associate Data Engineer role is entry-level, focusing on supporting the development and maintenance of data pipelines and platforms while collaborating with experienced practitioners.
Responsibilities:
• Support the development and maintenance of data pipelines used for analytics, reporting, and machine learning
• Assist with extracting, transforming, and loading (ETL/ELT) data from multiple sources into data platforms
• Contribute to data cleansing, validation, and transformation activities using Python and SQL
• Help prepare datasets for downstream consumption by analytics and data science teams
• Support batch and, where applicable, near-real-time data processing workflows under guidance
• Collaborate with data engineers, data scientists, and other team members in Agile delivery environments
• Build data engineering skills through training, mentorship, and hands-on delivery experience
• Work with functional and technical team members to help integrate data solutions into client business environments
Qualifications:
Required:
• Strong foundation in computer science fundamentals, including data structures and algorithms
• Strong analytical and problem-solving skills with attention to data quality and reliability
• Comfortable working onsite in a collaborative, team-based environment
• Ability to work effectively in a technology-driven consulting environment where tools, platforms, and client needs evolve over time
• Strong analytical and problem-solving skills, with the ability to approach complex tasks using structured, logical thinking
• Ability to learn new systems and technologies quickly and apply them in a delivery setting
• Proficiency in Python (preferred) or another programming language used for data processing
• Hands-on experience using data manipulation tools such as pandas, NumPy, and SQL, gained through coursework, labs, projects, or internships
• Ability to write clear, maintainable code for data transformation and processing tasks
• Understanding of ETL/ELT concepts and how data moves from source systems to consumption layers
• Familiarity with relational databases and SQL for querying and data manipulation
• Basic understanding of data modeling concepts such as schemas, normalization, or dimensional models
• Exposure to cloud-based data or analytics platforms (e.g., AWS, Azure, or Google Cloud) through coursework, labs, or projects
• Familiarity with core cloud data services such as object storage, databases, or analytics services
• Ability to translate business or functional requirements into technical solutions, with guidance from senior team members
• Comfortable working onsite in a collaborative, team-based environment
• Strong willingness to learn, accept feedback, and continuously improve
• Familiarity with generative AI concepts, including basic modeling approaches, responsible use, and ethical considerations, gained through coursework, projects, or self-study
Preferred:
• Master's Degree
• Exposure to distributed data processing tools such as Apache Spark or PySpark
• Familiarity with modern data warehouse technologies (e.g., Snowflake, Redshift, BigQuery)
• Exposure to streaming or event-based data concepts
• Familiarity with version control tools such as Git
• Basic awareness of how data engineering supports machine learning workflows
Company:
IBM provides technology and consulting, including software, infrastructure systems, and cloud-based solutions. Founded in 1911, the company is headquartered in Armonk, USA, with a team of 10001+ employees. The company is currently Late Stage.

What IBM employees say

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Benefits

Hours and flexibility

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About IBM

Sourced by ZipRecruiter

At IBM, work is more than a job - it's a calling: To build. To design. To code. To consult. To think along with clients and sell. To make markets. To invent. To collaborate. Not just to do something better, but to attempt things you've never thought possible. Are you ready to lead in this new era of technology and solve some of the world's most challenging problems? If so, lets talk.

Industry

It services

Company size

10,000+ Employees

Headquarters location

Armonk, NY, US

Year founded

1911

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