1

Data Preprocessing Jobs (NOW HIRING)

Data Engineer

Phoenix, AZ · On-site

$113K - $136K/yr

Python, Java, C++, JavaScript • Experience with big data preprocessing and transformation tools and process Preferred : • 1+ year of experience in big data technologies (Cassandra, HBase, Spark ...

... data preprocessing, feature engineering, and model evaluation • Experience working with APIs, large datasets, and enterprise systems • Strong proficiency in Python and SQL • Experience ...

Exposure to data preprocessing tools (Pandas, NumPy) * Basic cloud AI services Note : Please inform the candidates to brush up on the knowledge in Copilot as well if not aware of. The python coding ...

Should have the ability to clearly express ideas Experience working with Agile Methodology Knowledge on Textual data preprocessing Generating embeddings/tokenization Understanding on transfer based ...

Mlops Engineer - only W2

Minneapolis, MN · On-site

$119K - $143K/yr

Writing SQL queries for data preprocessing and post-processing tasks * Developing Python-based workflows to integrate and orchestrate multiple pipeline components * Deploying, monitoring, and ...

Showing results 21-40

Data Preprocessing information

See salary details

$46K

$165K

$243.5K

How much do data preprocessing jobs pay per year?

As of Aug 22, 2026, the average yearly pay for data preprocessing 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 data preprocessing?

Data preprocessing is the process of cleaning, transforming, and organizing raw data into a usable format for analysis or machine learning. It involves steps such as handling missing values, removing duplicates, normalizing or scaling data, and encoding categorical variables. Proper data preprocessing helps improve the quality and performance of predictive models by ensuring the data is accurate, consistent, and suitable for analysis.

What are the key skills and qualifications needed to thrive as a data preprocessing specialist, and why are they important?

To thrive as a Data Preprocessing Specialist, you need a strong background in statistics, data cleaning, and data transformation, often supported by a degree in computer science, data science, or a related field. Proficiency with tools such as Python (pandas, NumPy), SQL, and data visualization platforms is typically essential, along with familiarity with data management systems. Attention to detail, problem-solving abilities, and effective communication are standout soft skills in this position. These skills are crucial for ensuring high-quality, reliable datasets that underpin accurate data analysis and machine learning outcomes.

What are some common challenges faced in a data preprocessing role, and how can they be effectively managed?

Professionals in Data Preprocessing often encounter challenges such as handling incomplete or inconsistent data, managing large datasets, and ensuring data quality before analysis. Addressing these issues typically involves using specialized tools to automate data cleaning, establishing clear data validation rules, and collaborating closely with data engineers and analysts. Staying updated with best practices and leveraging scripting languages like Python or R can also streamline the preprocessing workflow, making it easier to deliver reliable and accurate datasets for downstream analysis.

What is the difference between Data Preprocessing vs Data Analysis?

AspectData PreprocessingData Analysis
Primary FocusCleaning, transforming, and preparing raw data for analysisInterpreting data to extract insights and support decision-making
Skills RequiredData cleaning, scripting, understanding of data formatsStatistical analysis, data visualization, critical thinking
Work EnvironmentData engineering teams, data science projectsBusiness intelligence, research, data science teams
Tools UsedPython, R, SQL, ETL toolsExcel, Tableau, R, Python, statistical software

While data preprocessing involves preparing raw data for analysis by cleaning and transforming it, data analysis focuses on interpreting the prepared data to uncover trends and insights. Both roles are essential in the data pipeline but serve different purposes in the data lifecycle.

More about Data Preprocessing jobs

What cities are hiring for Data Preprocessing jobs?

Cities with the most Data Preprocessing job openings:

What states have the most Data Preprocessing jobs?

States with the most job openings for Data Preprocessing jobs include:

Infographic showing various Data Preprocessing job openings in the United States as of August 2026, with employment types broken down into 100% Full Time. Highlights an 100% In-person job distribution, with an average salary of $165,018 per year, or $79.3 per hour.

$113K - $136K/yr

Full-time

Re-posted 11 days ago


Job description

Job Summary:
Intelliswift, an LTTS Company, is seeking a Data Engineer to build optimal cloud-based data pipelines and automated data ingestion processes. The role involves developing and deploying cloud-based web applications primarily using AWS services.
Responsibilities:
• Build optimal cloud-based data pipeline in AWS
• Build automated data ingestion and ETL processes
• Develop and deploy cloud-based web applications
Qualifications:
Required:
• Bachelor's Degree in Computer Science, Computer Engineering or Electrical Engineering with 5+ years of data engineering experience, Master's Degree is a plus
• 3+ years of experience with AWS cloud services: EC2, RDS, DynamoDB, Batch, EMR, Redshift
• 1+ years of Full-Stack web application development experience and User Interface (UI) design knowledge
• Experience with data pipeline and workflow management tools like Airflow
• Strong SQL and Database skills
• Solid experience with application development, testing and deployment processes and tools.
• Proficient in object-oriented/object function scripting languages: Python, Java, C++, JavaScript
• Experience with big data preprocessing and transformation tools and process
Preferred:
• 1+ year of experience in big data technologies (Cassandra, HBase, Spark, Hadoop, HDFS)
• Experience with Python web frameworks such as Django or Flask
Company:
"Intelliswift, an LTTS Company, delivers world-class Digital Product Engineering, Data Management, Analytics & AI, and Digital Ent Solutions It is a sub-organization of L&T Technology Services, Ltd.. Founded in 2001, the company is headquartered in Newark, USA, with a team of 1001-5000 employees. The company is currently Late Stage.