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Data Wrangler Full Time Jobs (NOW HIRING)

... Full-Time Equivalent (FTE) hours, compute costs, storage consumption, and infrastructure ... Proficient in deep learning, supervised and unsupervised learning techniques, data wrangling, and ...

Senior Data Engineer

Beverly, NJ · On-site

$102K - $139K/yr

Design and Develop ETL to extract data from first and third-party data sources, stitch, and wrangle ... Full-time associates are also eligible for paid time off, paid holidays and a 401(k) plan. We are a ...

... Full Time If Part Time how many hours per week Regular or Temporary Regular Position End Date (if ... Performing data wrangling and matching leveraging Extract Load Transfer (ETL) techniques

... Full-Time Career Level Staff Education Master's Degree Travel Security Clearance Required TS/SCI ... wrangling, and feature engineering. * Experience with data provenance tracking, model ...

Senior Data Engineer

Edgewater Park, NJ · On-site

$80K - $105K/yr

Design and Develop ETL to extract data from first and third-party data sources, stitch, and wrangle ... Full-time associates are also eligible for paid time off, paid holidays and a 401(k) plan. We are a ...

Data Analyst 1

Schenectady, NY · On-site

$66K - $85K/yr

... data wrangling techniques (joining, merging, stacking, cleansing, transposing, aggregating ... working full-time for a qualifying employer. For more information on PSLF, please visit www ...

Prepare data for analysis and reporting using data wrangling techniques (joining, merging, stacking ... working full-time for a qualifying employer. For more information on PSLF, please visit www ...

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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 Jun 10, 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 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 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:
Data Science Specialist

Data Science Specialist

Adidev Technologies Inc

Manhattan, NY • Remote

Full-time

Posted 19 days ago


Job description

Adidev Technologies Inc 

www.adidevtechnologies.com

URGENT HIRE - HIRING PROCESS - 24-48 HOURS!

Adidev Technologies is seeking 1-2 yrs of relevant experience in Data Science. A project can last anywhere from 6 months to 18 months. Salary varies depending on experience, and we are in search of candidates looking to start as soon as possible. Excellent written and oral communication are required as is the ability to work well in a team environment.

If you are looking for a new challenge and are ready to make an impact on a growing team, then this will be a perfect fit. As a Data Scientist/Data Science Specialist for Adidev Technologies Inc., you will be enhancing and debugging large-scale applications for one of our well-known clients.

Adidev Technologies is a growing software consulting company that is constantly expanding. As we are working with renowned clients and ready to take on new ones, we are seeking brilliant software engineers. Not only do we offer a great team to work with, but we also offer you an opportunity to make an immediate impact and get rewarded accordingly

 

Job Description

  • Demonstrated experience using machine learning, deep learning, statistical methodology, and simulation/optimization modeling in geospatial, network topography, recommendation systems, environmental systems, and/or agronomic problems.
  • Strong foundation in Python programming in a cloud environment.
  • Strong quantitative abilities, distinctive problem-solving, and excellent analysis skills
  • Expertise in data wrangling using SQL,
  • Practical knowledge and experience with cloud-computing systems and platforms, including the routine deployment of pipelines through Kubernetes
  • Fluency in querying/extracting/aggregating data via SQL scripting.
  • Extract, load and transform data (ETL) from structured and unstructured sources
  • Apply Natural Language Processing and Computer Vision to solve business use cases,
  • Strong skills in scientific data analyses, modeling, visualization and communication of results.
  • Knowledge of Python libraries (NumPy, Pandas, SciKit-Learn, TensorFlow, PyTorch), Spacy, MongoDB, PostgreSQL, Flask, streamlet and a good knowledge of data pipelines construction
  • Ph.D., M.S. or B.S. in Computer Science, Computational Physics, Operations Research, Geospatial Sciences, Remote Sensing Science, Environmental Sciences, Computational Astronomy or related scientific discipline


Must  have 

  • Understanding of various machine learning algorithms (e.g. SVM, Random Forests, Gradient Boosting, Log-Log regression, XGBoost, Lasso, Ridge, Clustering techniques, Neural Networks and others)
  • Regression (e.g. ? Linear/Logistic/MNL/Mixed Effects/Regularization)
  • Classification (K-means, Hierarchical, Latent Class, DBScan, SVM)
  • Dimension Reduction techniques (Principal Component analysis, Singular Value Decomposition etc.)
  • Optimization (Linear programming, Stochastic Gradient Descent, Genetic Algorithm etc.)
  • Experience with neural network approaches to text classification CNN, RNN, LSTM,Keras
  • Machine Learning algorithms? Neural Networks, Naïve Bayes, Bagging & Boosting, Random Forest
  • Distributed computing tools and cloud technology (AWS)

QUALIFICATIONS

  • Degree in Data Science, Computer Science, Engineering, Math, or Statistics preferred
  • At least 2 yrs of relevant experience in Data Science


SKILLS

  • SQL, statistical modeling, Feature engineering, Data visualization, Deploying models to production, Python programming, AWS, Domains(Healthcare/ Manufacturing/ Marketing/ Financial/ Telecommunication), powerbi/tableau, data warehouse

Benefits

  • Competitive Salary

  • Paid Relocation

  • Remote Support

  • Guaranteed Regular Salary Reviews

  • Job Type: W2 or Contract 1099 (full-time - 40 hours)

Employment Type: FULL_TIME