ZipRecruiter

Log In

1

Data Engineer Python Jobs (NOW HIRING)

Next Step Systems

Data Engineer, Python & ETL

Chicago, IL · On-site

$118K - $141.60K/yr

Data Engineer, Python & ETL, Chicago, IL A proprietary trading firm is seeking a Data Engineer, Python & ETL to join its Data Infrastructure team, to help improve and extend the data platform. This ...

Princeton IT Services

$102.10K - $122.70K/yr

Lead Data Engineer Python, PySpark & SQL Location: Canada Job Type: Full time contract We are looking for a strong Lead Data Engineer with deep experience in Python, PySpark, SQL, and AWS to design ...

Take-Two Interactive

Data Engineer (Python/Spark)

Austin, TX · On-site

$113.50K - $136.30K/yr

They are seeking a dynamic Data Engineer to design, build, and maintain reliable and scalable data ... Required : • 3+ years of hands-on experience in Python. • 3+ years of hands-on experience in ...

ComboCurve, Inc.

Senior Data Engineer, Python

Houston, TX · On-site +1

$109.30K - $131.30K/yr

... of deep Python expertise, mastery of modern data processing and API frameworks, and a strong foundational understanding of mathematics, reasoning, and petroleum engineering principles.

Redolent, Inc.

Data Engineer

Sunnyvale, CA · On-site

$136.50K - $163.90K/yr

Data Engineer ( python, pyspark, scala, airflow) Location:Sunnyvale CA ( Hybrid ) Duration: 6 to 12+ Months Rate: DOE Bachelor or master's degree in computer science, Software Engineering, or a ...

next page

Showing results 1-20

People also search for

All JobsData Engineer Python Jobs

Data Engineer Python information

See salary details

$23K

$140K

$202.5K

How much do data engineer python jobs pay per year?

As of May 29, 2026, the average yearly pay for data engineer python in the United States is $139,971.00, according to ZipRecruiter salary data. Most workers in this role earn between $110,500.00 and $164,500.00 per year, depending on experience, location, and employer.

What is a Data Engineer Python job?

A Data Engineer Python job involves designing, building, and maintaining data pipelines using Python. These professionals ensure data is collected, processed, and stored efficiently for analytics and machine learning. They work with databases, cloud platforms, and big data technologies to optimize data workflows. Strong Python skills, SQL knowledge, and experience with ETL processes are essential for this role.

What are the key skills and qualifications needed to thrive in the Data Engineer Python position, and why are they important?

To thrive as a Data Engineer Python, you need strong programming skills in Python, a solid understanding of data modeling, ETL processes, and often a degree in computer science or a related field. Experience with big data tools like Apache Spark or Hadoop, cloud data platforms such as AWS or Azure, and certifications in data engineering are valuable assets. Analytical thinking, attention to detail, and effective communication are important soft skills for collaborating across teams and solving complex data challenges. These qualifications are critical for successfully designing, building, and maintaining scalable data pipelines that support organizational decision-making.

What are the typical daily responsibilities of a Data Engineer Python?

As a Data Engineer Python, your daily tasks will often include designing, building, and maintaining robust data pipelines to collect, process, and store large sets of structured and unstructured data. You’ll frequently work with Python to automate data workflows and ensure data quality, while also collaborating with data scientists, analysts, and other engineering teams to support shared objectives. Monitoring system performance, troubleshooting issues, and optimizing data processes for scalability and efficiency are also key parts of the role. This position offers an engaging mix of technical problem-solving and cross-functional teamwork in a dynamic data-driven environment.
More about Data Engineer Python jobs
What cities are hiring for Data Engineer Python jobs? Cities with the most Data Engineer Python job openings:
What are the most commonly searched types of Data Engineer Python jobs? The most popular types of Data Engineer Python jobs are:
What states have the most Data Engineer Python jobs? States with the most job openings for Data Engineer Python jobs include:
What job categories do people searching Data Engineer Python jobs look for? The top searched job categories for Data Engineer Python jobs are:
Data Engineer Python jobs near you
Infographic showing various Data Engineer Python job openings in the United States as of May 2026, with employment types broken down into 63% Full Time, and 37% Contract. Highlights an 81% In-person, 15% Hybrid, and 4% Remote job distribution, with an average salary of $139,971 per year, or $67.3 per hour.
Data Engineer (Python)

Data Engineer (Python)

Noblesoft Technologies

Auburn Hills, MI • On-site

$108.40K - $130.10K/yr

Contractor

Posted 26 days ago

Job description

Job Role: Senior Data Engineer (Python)

Location: Auburn Hills, MI
 

Mandatory Skills: Data Engineering, Python, PySpark, CI/CD, Airflow, Workflow Orchestration

Overall Experience: 8+ years of relevant experience

JOB REQUIREMENTS -

The Senior Data Engineer & Technical Lead (SDET Lead) will play a pivotal role in delivering major data engineering initiatives within the Data & Advanced Analytics space. This position requires hands-on expertise in building, deploying, and maintaining robust data pipelines using Python, PySpark, and Airflow, as well as designing and implementing CI/CD processes for data engineering projects

Key Responsibilities
1. Data Engineering: Design, develop, and optimize scalable data pipelines using Python and PySpark for batch and streaming workloads.
2. Workflow Orchestration: Build, schedule, and monitor complex workflows using Airflow, ensuring reliability and maintainability.
3. CI/CD Pipeline Development: Architect and implement CI/CD pipelines for data engineering projects using GitHub, Docker, and cloud-native solutions.
4. Testing & Quality: Apply test-driven development (TDD) practices and automate unit/integration tests for data pipelines.
5. Secure Development: Implement secure coding best practices and design patterns throughout the development lifecycle.
6. Collaboration: Work closely with Data Architects, QA teams, and business stakeholders to translate requirements into technical solutions.
7. Documentation: Create and maintain technical documentation, including process/data flow diagrams and system design artifacts.
8. Mentorship: Lead and mentor junior engineers, providing guidance on coding, testing, and deployment best practices.
9. Troubleshooting: Analyze and resolve technical issues across the data stack, including pipeline failures and performance bottlenecks.
Cross-Team Knowledge Sharing: Cross-train team members outside the project team (e.g., operations support) for full knowledge coverage.

Includes all above skills, plus the following;
·         Minimum of 7+ years overall IT experience
·         Experienced in waterfall, iterative, and agile methodologies

Technical Experience:

1. Hands-on Data Engineering : Minimum 5+ years of practical experience building production-grade data pipelines using Python and PySpark.
2. Airflow Expertise: Proven track record of designing, deploying, and managing Airflow DAGs in enterprise environments.
3. CI/CD for Data Projects : Ability to build and maintain CI/CD pipelines for data engineering workflows, including automated testing and deployment**.
4. Cloud & Containers: Experience with containerization (Docker and cloud platforms (GCP) for data engineering workloads. Appreciation for twelve-factor design principles
5. Python Fluency : Ability to write object-oriented Python code manage dependencies, and follow industry best practices
6. Version Control: Proficiency with **Git** for source code management and collaboration (commits, branching, merging, GitHub/GitLab workflows).
7. Unix/Linux: Strong command-line skills** in Unix-like environments.
8. SQL : Solid understanding of SQL for data ingestion and analysis.
9. Collaborative Development : Comfortable with code reviews, pair programming and using remote collaboration tools effectively.
10. Engineering Mindset: Writes code with an eye for maintainability and testability; excited to build production-grade software
11. Education: Bachelor’s or graduate degree in Computer Science, Data Analytics or related field, or equivalent work experience.

Unique Skills

• Graduate degree in a related field, such as Computer Science or Data Analytics
• Familiarity with Test-Driven Development (TDD)
• A high tolerance for OpenShift, Cloudera, Tableau, Confluence, Jira, and other enterprise tools