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Entry Level Data Engineering Jobs in Dallas, TX (NOW HIRING)

Perform data preprocessing, feature engineering, model training, and evaluation. * Build AI/ML ... entry level candidates are welcome , provided they have practical AI/ML projects and strong ...

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Product Engineering Technician

Lewisville, TX · On-site

$25/hr

  • Medical

  • Dental

  • Vision

  • PTO

Collect and track production, yield, and quality data * Assist engineers with testing, pilot runs ... We provide candidates with levels of experience ranging from executive to entry level. VSSI ...

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Structural Project Engineer (Entry-Level)

Decatur, TX · On-site

$85K - $100K/hr

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

Build Your Career in Structural Engineering At Clark Pacific, you'll do more than design buildings ... Work on hospitals, data centers, manufacturing facilities, parking structures, and commercial ...

Showing results 21-40

Entry Level Data Engineering information

See Dallas, TX salary details

$11

$20

$31

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

As of Aug 15, 2026, the average hourly pay for entry level data engineering in Dallas, TX is $20.02, according to ZipRecruiter salary data. Most workers in this role earn between $16.15 and $21.63 per hour, depending on experience, location, and employer.

What is an entry level data engineer?

An Entry Level Data Engineering job involves designing, building, and maintaining data pipelines that collect, process, and store data for analysis. Professionals in this role work with databases, ETL (Extract, Transform, Load) processes, and cloud platforms to ensure data is accessible and reliable. They often collaborate with data analysts and scientists to support business intelligence and machine learning initiatives. Common skills include SQL, Python, and experience with big data tools like Apache Spark or AWS. This role serves as a foundation for more advanced data engineering positions.

What types of projects and tasks can I expect to work on as an entry level data engineer?

As an Entry Level Data Engineer, you will typically assist with building data pipelines, cleaning and preparing data for analysis, and supporting the migration of data into cloud or on-premises data warehouses. Your daily tasks may include collaborating with data analysts, troubleshooting data quality issues, and learning to automate data flow processes. You’ll often work alongside more senior engineers, gaining exposure to real-world datasets and the software engineering practices that keep data infrastructure running smoothly. This hands-on experience offers a solid foundation for advanced data engineering roles as your career progresses.

What does an entry level data engineer do?

An entry level data engineer designs, builds, and maintains data pipelines and infrastructure to support data collection, storage, and processing. They work with tools like SQL, Python, and cloud platforms to ensure data is accessible and reliable for analysis and decision-making. This role often involves collaborating with data scientists and analysts to optimize data workflows and improve data quality.

What are the key skills and qualifications needed to thrive as an entry level data engineer?

To thrive as an Entry Level Data Engineer, you need a solid understanding of programming languages like Python or SQL, basic data modeling, and a relevant degree such as computer science or information technology. Familiarity with ETL tools, cloud platforms like AWS or Azure, and introductory certifications in big data technologies can be advantageous. Attention to detail, strong problem-solving abilities, and effective communication skills are valuable soft skills for this role. These competencies enable you to process and manage large data sets accurately, collaborate with teams, and support data-driven decision-making.

What are the most commonly searched types of Data Engineering jobs in Dallas, TX?

The most popular types of Data Engineering jobs in Dallas, TX are:

What are popular job titles related to Entry Level Data Engineering jobs in Dallas, TX?

For Entry Level Data Engineering jobs in Dallas, TX, the most frequently searched job titles are:

What job categories do people searching Entry Level Data Engineering jobs in Dallas, TX look for?

The top searched job categories for Entry Level Data Engineering jobs in Dallas, TX are:

What cities near Dallas, TX are hiring for Entry Level Data Engineering jobs?

Cities near Dallas, TX with the most Entry Level Data Engineering job openings:

Infographic showing various Entry Level Data Engineering job openings in Dallas, TX as of August 2026, with employment types broken down into 88% Full Time, and 12% Part Time. Highlights an 100% In-person job distribution, with an average salary of $41,645 per year, or $20 per hour.

Acceleration Center- Agentic AI and Machine Learning Developer- Senior Associate

Pwc

Dallas, TX

$77K - $202K/yr

Full-time

Medical, Dental, Vision, Retirement, PTO

Posted 18 days ago


PwC rating

8.3

Company rating: 8.3 out of 10

Based on 76 frontline employees who took The Breakroom Quiz

26th of 72 rated business consultants


Job description

Industry/Sector

Not Applicable

Specialism

Risk Architecture

Management Level

Senior Associate

Job Description & Summary

The Opportunity
As an Acceleration Center- Agentic AI and Machine Learning Developer- Senior Associate, you will play a pivotal role in transforming raw data into actionable insights, enabling informed decision-making and driving business growth. Within our Risk & Regulatory practice, you will apply data, algorithms, and software engineering to build and deploy AI and Machine Learning solutions at scale. As a Senior Associate, you will focus on building meaningful client connections and learning how to manage and inspire others. You will navigate increasingly complex situations, growing your personal brand and deepening your technical skills. You are expected to anticipate the needs of your teams and clients, and to deliver quality work.
In this role at PwC, you will design AI systems, engage in data wrangling, and implement software to enable scalable AI models. You will use a broad range of tools and methodologies to generate new ideas and solve problems, while developing a deeper understanding of the business context and how it is evolving. Your work will contribute to the broader objectives of your projects, fitting into the overall strategy and reinforcing professional and technical standards.
Responsibilities
- Designing and implementing AI and machine learning solutions to transform raw data into actionable insights
- Developing scalable software and platform systems using advanced algorithms and data engineering techniques
- Collaborating with clients to understand their needs and deliver tailored data solutions
- Utilizing programming languages such as Python and Java to build and deploy AI models
- Integrating data from various sources to enhance data quality and infrastructure
- Applying machine learning libraries like TensorFlow and Scikit-Learn to optimize model performance
- Conducting complex data analysis to support informed decision-making and business growth
- Building and maintaining data pipelines to streamline data processing and analysis
- Leveraging natural language processing tools to develop innovative text analytics solutions
- Mentoring junior team members and guiding them in technical and professional development
What You Must Have
- At least a Bachelor's degree
- At least 2 years of experience
What Sets You Apart
- Preference for at least one of the following fields of study: Analytics/Data Science, Artificial Intelligence/Robotics, Computer Science/Information Systems, Engineering
- At least one of the following: Certifications aligned to data engineering, machine learning, and cloud platforms, including AWS, Google Cloud, Microsoft Azure, Databricks, Snowflake, or related data and AI credentials
- Demonstrating proficiency in AI implementation and machine learning libraries
- Utilizing Python and Java for complex data analysis and modeling
- Excelling in data integration and data pipeline development
- Applying natural language processing techniques for text analytics
- Leveraging TensorFlow and Scikit-Learn for deep learning projects

Travel Requirements

Up to 60%

Job Posting End Date

The salary range for this position is: $77,000 - $202,000. Actual compensation within the range will be dependent upon the individual's skills, experience, qualifications and location, and applicable employment laws. All hired individuals are eligible for an annual discretionary bonus. PwC offers a wide range of benefits, including medical, dental, vision, 401k, holiday pay, vacation, personal and family sick leave, and more. To view our benefits at a glance, please visit the following link: https://pwc.to/benefits-at-a-glanceAs PwC is anequal opportunity employer, all qualified applicants will receive consideration for employment at PwC without regard to race; color; religion; national origin; sex (including pregnancy, sexual orientation, and gender identity); age; disability; genetic information (including family medical history); veteran, marital, or citizenship status; or, any other status protected by law.PwC does not intend to hire experienced or entry level job seekers who will need, now or in the future, PwC sponsorship through the H-1B lottery, except as set forth within the following policy: https://pwc.to/H-1B-Lottery-Policy.Learn more about how we work: https://pwc.to/how-we-workFor only those qualified applicants that are impacted by the Los Angeles County Fair Chance Ordinance for Employers, the Los Angeles' Fair Chance Initiative for Hiring Ordinance, the San Francisco Fair Chance Ordinance, San Diego County Fair Chance Ordinance, and the California Fair Chance Act, where applicable, arrest or conviction records will be considered for Employment in accordance with these laws. At PwC, we recognize that conviction records may have a direct, adverse, and negative relationship to responsibilities such as accessing sensitive company or customer information, handling proprietary assets, or collaborating closely with team members. We evaluate these factors thoughtfully to establish a secure and trusted workplace for all.

What PwC employees say

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