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Seasonal Data Engineer Python Jobs (NOW HIRING)

Data Engineer

$117K - $140K/yr

Data Engineer/ Python/Pyspark/ SQL/ ETL/ DBT (Data Build Type)/ AWS Position Summary: The Senior Data Engineer leads complex data engineering projects, working on designing data architectures that ...

Data Engineer - Python/AI

Addison, IL · On-site

$114K - $137K/yr

Identifies, defines, and documents data engineering requirements, communicating required ... development in Python * 3+ years of handson AI/ML experience , building and deploying machine ...

AWS Data Engineer

Atlanta, GA · On-site

$80K - $120K/yr

Qualifications (Data Engineer/Python Developer) * 10+ years hands-on Python development experience for big data application. * Extensive working experience in implementing scalable and efficient data ...

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Seasonal Data Engineer Python information

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$46K

$165K

$243.5K

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

As of Sep 15, 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:

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States with the most job openings for Seasonal Data Engineer Python jobs include:

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For Seasonal Data Engineer Python jobs, the most frequently searched job titles are:

What other helpful pages are available for Seasonal Data Engineer Python?

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Apex Informatics
IT Services • 1 - 10 employees

$117K - $140K/yr

Contractor

Re-posted 19 days ago


Job description

Title: Senior Data Engineer
Location: Remote

Duration: 06 Months (C2H Role)
Main Skills: Data Engineer/ Python/Pyspark/ SQL/ ETL/ DBT (Data Build Type)/ AWS
Position Summary:
The Senior Data Engineer leads complex data engineering projects, working on designing data architectures that align with business requirements. This role focuses on optimizing data workflows, managing data pipelines, and ensuring the smooth operation of data systems.
Minimum Qualifications:
• 8+ Years overall IT experience with minimum 5 years of work experience in below tech skills
• Tech Skills:
§ Strong experience in Python Scripting and PySpark for data processing
§ Proficiency in SQL, dealing with big data over Informatica ETL
§ Proven experience in Data quality and data optimization of data lake in Iceberg format, with strong understanding of architecture
§ Experience in AWS cloud platform and its data services (S3, Redshift, Lambda, EMR, Airflow, Postgres, SNS, Event bridge)
§ Expertise in BASH/Shell scripting
§ Experience in Data Build Tool (DBT) or similar data transformation tools
§ Experience in Mulesoft API
§ Nice to have: Kafka, Tableau
• Strong understanding of healthcare data systems and experience leading data engineering teams
• Experience in Agile environments.
• Excellent problem-solving skills and attention to detail.
• Effective communication and collaboration skills.
Responsibilities:
  • Leads development of data pipelines and architectures that handle large-scale data sets.
  • Designs, constructs, and tests data architecture aligned with business requirements.
  • Provides technical leadership for data projects, ensuring best practices and high-quality data solutions.
  • Collaborates with product, finance, and other business units to ensure data pipelines meet business requirements.
  • Work with DBT (Data Build Tool) for transforming raw data into actionable insights.
  • Oversees development of data solutions that enable predictive and prescriptive analytics.
  • Ensures the technical quality of solutions, managing data as it moves across environments.
  • Aligns data architecture to Healthfirst solution architecture.