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Data Wrangling Jobs (NOW HIRING)

Reflexive Concepts

... wrangling, SQL/NoSQL database management (PostgreSQL, MongoDB), and data visualization tools such as Tableau and Matplotlib. Qualifications: * Bachelor's degree from an accredited college or ...

4pconsultinginc

Data Scientist III (IT)

Birmingham, AL · On-site

The ideal candidate has hands-on experience with data wrangling, exploratory data analysis, statistical modeling, machine learning algorithms, and data visualization , and can work effectively with ...

4P Consulting Inc.

Data Scientist

Atlanta, GA

Responsibilities include data wrangling, data analysis, and data exploration. Should be familiar with a variety of Machine Learning algorithms and big data processing frameworks. In addition to ...

Sonsoft Inc

Data Wrangler

New York, NY · On-site

Experience in Data wrangling,ability to analyze the data provide insights * Good communication skills, work with business users gather requirements. * Knowledge on Hadoop ecosystems & SQL knowledge

Sonsoft Inc

Data Wrangler

New York, NY · On-site

Experience in Data wrangling,ability to analyze the data provide insights * Good communication skills, work with business users gather requirements. * Knowledge on Hadoop ecosystems & SQL knowledge

TriOptus LLC

Sr. Data Analyst - Commerce Domain

Dallas, TX · On-site

$79.40K - $100.10K/yr

Analytics, Reporting, Data Wrangling, creation of dashboard for web and omni channel activities. * Develop & maintain operational reports and dashboards in Adobe Cloud, Quantum Metrics, Tableau or ...

Sonsoft Inc

Data Wrangler

New York, NY · On-site

Experience in Data wrangling,ability to analyze the data provide insights * Good communication skills, work with business users gather requirements. * Knowledge on Hadoop ecosystems & SQL knowledge

Megan soft Inc

Data Scientist(W2 Position)

Dearborn, MI · On-site

Experience using SQL for acquiring and transforming real-world data, data cleaning, data collection or other data wrangling challenges Thanks & Regards Praveen Megan Soft, Inc. Direct No: +1(248) 266 ...

SRP Systems Inc

Senior Data Scientist

Princeton, NJ · On-site

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 ...

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Data Wrangling information

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$44.5K

$129.7K

$177.5K

How much do data wrangling jobs pay per year?

As of May 29, 2026, the average yearly pay for data wrangling in the United States is $129,716.00, according to ZipRecruiter salary data. Most workers in this role earn between $114,500.00 and $137,500.00 per year, depending on experience, location, and employer.

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 analytical skills, proficiency in data cleaning and transformation, and a background in statistics or computer science. Expertise in tools such as Python, R, SQL, and data processing libraries, as well as familiarity with ETL processes, is typically required. Attention to detail, problem-solving abilities, and effective communication help ensure data accuracy and facilitate collaboration across teams. These skills are crucial for preparing reliable datasets that support accurate analysis and informed decision-making within organizations.

What are some common challenges faced by data wranglers in preparing datasets for analysis?

Data wranglers often encounter challenges such as dealing with incomplete, inconsistent, or messy datasets, which can require significant cleaning and transformation work. Identifying and correcting errors, managing missing values, and ensuring data from different sources can be integrated smoothly are frequent tasks. Additionally, data wranglers must maintain data integrity and document their processes to facilitate collaboration with analysts, data scientists, and other stakeholders. Overcoming these challenges requires attention to detail, strong problem-solving skills, and effective communication within the team.

What is data wrangling?

Data wrangling, also known as data munging, is the process of cleaning, transforming, and organizing raw data into a usable format for analysis. This involves identifying and correcting errors, handling missing values, and restructuring data sets to meet the needs of data analysis or machine learning. Data wrangling is a crucial step in the data pipeline, as quality and well-structured data are essential for accurate insights and decision-making. The process can be performed manually or automated using specialized software and programming languages like Python or R.

What is the difference between Data Wrangling vs Data Analysis?

AspectData WranglingData Analysis
Primary FocusCleaning, transforming, and preparing raw dataInterpreting data to extract insights
Skills NeededData cleaning, scripting, database skillsStatistical analysis, visualization, interpretation
Tools Commonly UsedPython, R, SQL, ExcelExcel, Tableau, R, Python
Work EnvironmentData engineering teams, data warehousesBusiness intelligence, research teams

While data wrangling involves preparing raw data for analysis by cleaning and transforming it, data analysis focuses on interpreting that data to generate insights. Both roles often overlap but serve different stages in the data pipeline, with data wrangling being a foundational step for effective data analysis.

More about Data Wrangling jobs
What cities are hiring for Data Wrangling jobs? Cities with the most Data Wrangling job openings:
What states have the most Data Wrangling jobs? States with the most job openings for Data Wrangling jobs include:
What job categories do people searching Data Wrangling jobs look for? The top searched job categories for Data Wrangling jobs are:
Data Wrangling jobs near you
Infographic showing various Data Wrangling job openings in the United States as of May 2026, with employment types broken down into 1% As Needed, 98% Full Time, and 1% Temporary. Highlights an 86% Physical, 3% Hybrid, and 11% Remote job distribution, with an average salary of $129,716 per year, or $62.4 per hour.
Data Scientist II

Data Scientist II

Reflexive Concepts

On-site

Other

Posted 26 days ago

Job description

Reflexive Concepts is seeking a Data Scientist to join our team!
Specifically, we are looking for a Data Scientist with proficiency in Python and R, strong statistical analysis and machine learning skills (TensorFlow, Scikit-Learn), and experience in data wrangling, SQL/NoSQL database management (PostgreSQL, MongoDB), and data visualization tools such as Tableau and Matplotlib.
Qualifications:
  • Bachelor's degree from an accredited college or university in a quantitative discipline (e.g., statistics, mathematics, operations research, engineering or computer science)
  • Five (5) years of experience analyzing datasets and developing analytics, five (5) years of experience programming with data analysis software such as R, Python, SAS, or MATLAB
    • An additional four (4) years of experience in software development, cloud development, analyzing datasets, or developing descriptive, predictive, and prescriptive analytics can be substituted for a Bachelor's degree
    • A PhD from an accredited college or university in a quantitative discipline can be substituted for four (4) years of experience
Required:
  • Programming Languages: Proficiency in programming languages such as Python and R is crucial for data manipulation, analysis, and implementing algorithms. Python is favored for its simplicity and extensive libraries (like NumPy and pandas), while R is preferred for statistical analysis and data visualization
  • Statistical Analysis: A strong foundation in statistics and probability is necessary for analyzing data accurately and making informed decisions. Understanding concepts like regression analysis, hypothesis testing, and statistical distributions is essential
  • Machine Learning: Knowledge of machine learning algorithms and frameworks (such as TensorFlow and Scikit-Learn) is vital for building predictive models and automating decision-making processes
  • Data Wrangling: The ability to clean and organize complex datasets is critical. Data wrangling involves transforming raw data into a usable format, which is often time-consuming but necessary for effective analysis
  • Database Management: Familiarity with SQL and database management systems (like PostgreSQL and MongoDB) is essential for extracting and manipulating data stored in relational databases
  • Data Visualization: Skills in data visualization tools (such as Tableau and Matplotlib) help communicate findings effectively. Creating charts, graphs, and dashboards is crucial for making data understandable to stakeholders

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