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Data Wrangler Full Time Jobs (NOW HIRING)

Senior Data Scientist: someone with 5+ years of full time, work experience as a data scientist solving complex problems. Must be highly experienced with data cleanups, data wrangling, data ...

Irving, TX - Fulltime Position Data Scientist with Generative AI Expertise * Programming languages ... Data wrangling & manipulation: SQL, data cleaning, feature engineering * Hyperscale's: AWS, Azure ...

Data Engineer

Dallas, TX · On-site

$113K - $136K/yr

The ideal candidate is an experienced data pipeline builder and data wrangler who enjoys optimizing ... Work Environment -In Office Job Type - Full Time Skills & Requirements Qualifications

Position Type: Full Time Task Description: This is a full-time 90% remote position, 10% to Brite ... Support end-to-end ML lifecycle from data wrangling and modeling to deployment and monitoring.

Position Type: Full Time Task Description: This is a full-time 90% remote position, 10% to Brite ... Support end-to-end ML lifecycle from data wrangling and modeling to deployment and monitoring.

Data Integrations Engineer

New York, NY · On-site

$125K - $139K/yr

Ad hoc data wrangling and sanitization * Monitor automated data alerts - prioritize, track, and ... All full-time regular employees receive a bonus target and are eligible to receive stock-based ...

Madison, WI Full Time (Direct Hire) • 5+ Years of total experience and 2-4 years of in-depth and ... wrangling, model development, software development, A/B Testing, Back Testing. • Extremely ...

About Contract Wrangler Contract Wrangler enables companies to maximize profit and minimize risk ... Our solution enables operating teams across an enterprise to act with real-time, data-driven ...

Madison, WI Full Time (Direct Hire) 5+ Years of total experience and 2-4 years of in-depth and ... Extremely proficient in Data Analysis, data wrangling, model development, software development, A/B ...

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Data Wrangler Full Time information

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$46K

$165K

$243.5K

How much do data wrangler full time jobs pay per year?

As of Jul 29, 2026, the average yearly pay for data wrangler full time in the United States is $165,018.00, according to ZipRecruiter salary data. Most workers in this role earn between $133,500.00 and $170,000.00 per year, depending on experience, location, and employer.

What is the difference between Data Wrangler Full Time vs Data Analyst?

AspectData Wrangler Full TimeData Analyst
Primary RoleCleaning, transforming, and preparing raw data for analysisInterpreting data, generating reports, and providing insights
Skills RequiredData cleaning, scripting (Python, SQL), data manipulationStatistical analysis, data visualization, reporting tools
Work EnvironmentData engineering teams, data pipelines, ETL processesBusiness teams, analytics departments, decision-making
Common CertificationsSQL, Python, data management certificationsExcel, Tableau, statistical analysis certifications

While Data Wrangler Full Time focuses on data preparation and cleaning, Data Analyst emphasizes analyzing data to generate insights. Both roles often collaborate but serve different stages of the data workflow.

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

To thrive as a Data Wrangler, you need strong skills in data analysis, data cleaning, and manipulation, often supported by a degree in computer science, statistics, or a related field. Proficiency with programming languages like Python or R, data wrangling libraries (such as pandas or dplyr), and experience with databases and ETL tools are typically required. Attention to detail, problem-solving ability, and effective communication are essential soft skills for translating raw data into actionable insights. These skills ensure that data is accurate, well-organized, and ready for downstream analysis, which is crucial for informed decision-making.

What is the difference between data analyst and data wrangler?

A data wrangler is responsible for collecting, cleaning, and organizing raw data to prepare it for analysis, often using tools like SQL, Python, or Excel. A data analyst interprets the cleaned data to generate insights, create reports, and support decision-making, typically requiring skills in statistical analysis and visualization. Both roles are essential in data-driven environments, with data wranglers focusing on data preparation and analysts on data interpretation.

What is the highest paying job in data?

In data-related fields, roles such as Data Science Director, Chief Data Officer, and Machine Learning Engineer tend to be among the highest paying positions, often earning six-figure salaries. These roles typically require advanced skills in statistics, programming, and data management, along with extensive experience and leadership responsibilities.

What are Data Wranglers?

Data Wranglers are professionals who specialize in collecting, cleaning, and organizing raw data so it can be easily analyzed and used by data scientists or analysts. Their work involves transforming messy, unstructured, or incomplete datasets into formats that are more usable and reliable for analysis. In a full-time role, Data Wranglers may also automate data pipelines, ensure data quality, and collaborate with other teams to support business intelligence and decision-making processes.

What jobs pay 4000 a week without a degree?

A Data Wrangler Full Time role typically does not pay $4,000 a week without a degree, as it is often an entry-level position focused on data management and cleaning. High-paying jobs that can reach this level without a degree include roles like sales managers, real estate brokers, or specialized trades such as commercial pilots or certain tech sales positions, which often require experience, skills, or certifications rather than formal degrees.

What is the difference between a data wrangler and a dit?

A data wrangler is a professional responsible for cleaning, organizing, and preparing raw data for analysis, often using tools like SQL, Python, or Excel. A DIT (Digital Imaging Technician) is a role in film and video production focused on managing and maintaining digital media assets. In the context of data-related jobs, a data wrangler's work involves data management, while a DIT's work relates to media and image handling.

What are some common challenges faced by Data Wranglers in a full-time position, and how are they typically addressed within a team environment?

Data Wranglers often encounter challenges such as dealing with inconsistent data formats, missing values, and integrating data from multiple sources. These issues are typically addressed through close collaboration with data engineers, analysts, and domain experts to clarify data requirements and resolve ambiguities. Teams often use standardized tools and best practices for data cleaning and validation, and regular communication helps ensure that any data quality issues are identified and tackled early in the workflow. Being proactive and detail-oriented, as well as participating in team knowledge sharing, greatly assists in overcoming these common hurdles.
More about Data Wrangler Full Time jobs
What are the most commonly searched types of Data Wrangler jobs? The most popular types of Data Wrangler jobs are:
Infographic showing various Data Wrangler Full Time job openings in the United States as of July 2026, with employment types broken down into 100% Full Time. Highlights an 68% In-person, 11% Hybrid, and 21% Remote job distribution, with an average salary of $165,018 per year, or $79.3 per hour.
Senior Data Scientist

Senior Data Scientist

SRP Systems Inc

Princeton, NJ • On-site

Full-time

Posted 16 days ago


Job description

Company Description
SRP is a big data startup company located in Princeton, NJ focused on Dynamic Pricing, run
by seasoned alumni from Stanford University and Wharton.
Job Description
Senior Data Scientist: someone with 5+ years of full time, work experience as a
data scientist solving complex problems. Must be highly experienced
with data cleanups, data wrangling, data transformation, feature
engineering, anomaly handling, model development, model tune-ups, metric
development to evaluate the model, ability to handle small data sets,
creative in handling tough data problems and so on. A python background
is desired, but we will also consider a R background. You should be able
to demonstrate your past expertise in handling difficult problems.
Qualifications
Additional Information
This is a Full time project