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Seasonal Data Engineer Python Jobs (NOW HIRING)

RIT Solutions, Inc.

Data Engineer/Python

Malvern, PA · Hybrid

$112.40K - $134.90K/yr

Data Engineer/Python MALVERN, PA - HYBRID Senior Data Engineer Location: Malvern, PA (Hybrid) Experience Level: Level 4 (8+ years) Role Summary We are seeking a highly motivated Senior Data Engineer ...

Diverse Lynx

Data Engineer - Python/PySpark

Tampa, FL · On-site

$125K/yr

Data Engineer - Python/PySpark Position: Data Engineer - Python/PySpark Location: Irving, TX and Tampa, FL Rate: $125K (Including QPLC) - 3-6 years of experience as a Data Engineer with strong Python ...

Omni Inclusive

Data Engineer - Python

Jersey City, NJ · On-site

Python (Pandas) Shell scripting, Pl/SQl, Unix shell scripting Exp: 10+ years Responsibilities ... Implement security measures and data protection protocols. * Troubleshoot, debug, and upgrade ...

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 ...

PLANIT Group

Data Engineer - Python

Washington, DC · On-site

$129.60K - $155.70K/yr

As a Data Engineer, you will play a crucial role in designing, developing, and maintaining our data infrastructure. Your expertise in Python, PySpark, ETL processes, CI/CD (Jenkins or GitHub), and ...

RIT Solutions

Data Engineer/Python

Malvern, PA · Hybrid

$112.40K - $134.90K/yr

Proven experience as a Data Engineer with a strong focus on data pipelines and ETL/ELT processes. * Expertise in Python (estimated 80-90% of development work). * Experience with AWS services ...

Samprasoft

Data Engineer (Python)

Smithfield, RI · On-site

$110K - $132.10K/yr

Data Engineer Industry: Banking & Financial Duration: 12 Months- Long term Location: Smithfield RI/ Durham, NC/ Westlake, TX Top Skills: Informatica, SQL, Snowflake, python Required Qualifications ...

Samprasoft

Data Engineer (Python)

Durham, NC · On-site

$103.70K - $124.60K/yr

Data Engineer Industry: Banking & Financial Duration: 12 Months- Long term Location: Smithfield RI/ Durham, NC/ Westlake, TX Top Skills: Informatica, SQL, Snowflake, python Required Qualifications ...

APN Consulting

Data Engineer - Python Developer

Oldwick, NJ · Hybrid

$125K - $150.10K/yr

Data Engineer - Python Developer APN Consulting, Inc. is a progressive IT staffing and services company offering innovative business solutions to improve client business outcomes. We focus on high ...

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Seasonal Data Engineer Python information

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How much do seasonal data engineer python jobs pay per year?

As of Jun 4, 2026, the average yearly pay for seasonal data engineer python 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 Seasonal Data Engineer Python vs Data Analyst?

AspectSeasonal Data Engineer PythonData Analyst
Required CredentialsBachelor's in CS, Data Science, or related; Python proficiency; SQL knowledgeBachelor's in Statistics, Math, or related; Excel, SQL, and data visualization skills
Work EnvironmentProject-based, often in tech or finance sectors, with focus on data pipelinesBusiness-focused, in various industries, analyzing data to inform decisions
Employer & Industry UsageTech companies, finance, retail during seasonal peaksCorporate, marketing, healthcare, and other sectors
Common Search & ComparisonYesYes

Seasonal Data Engineer Python roles focus on building and maintaining data pipelines using Python, especially during peak seasons. Data Analysts interpret data to generate insights and reports. While both roles require data skills, Data Engineers are more technical and infrastructure-oriented, whereas Data Analysts focus on analysis and visualization.

What cities are hiring for Seasonal Data Engineer Python jobs? Cities with the most Seasonal 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 Seasonal Data Engineer Python jobs? States with the most job openings for Seasonal Data Engineer Python jobs include:
Seasonal Data Engineer Python jobs near you
Data Engineer (Python)

Data Engineer (Python)

Noblesoft Technologies

Auburn Hills, MI • On-site

$108.40K - $130.10K/yr

Contractor

Posted yesterday

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