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Data Engineer (Python + Pyspark)
⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for a Data Engineer (Python + PySpark) in Charlotte, NC, offering a W2 contract. Requires 8-12 years of experience, strong skills in Apache Spark, Python, SQL, and Autosys, with a degree in Computer Science or related field.
🌎 - Country
United States
💱 - Currency
$ USD
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💰 - Day rate
Unknown
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🗓️ - Date
November 5, 2025
🕒 - Duration
Unknown
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🏝️ - Location
On-site
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📄 - Contract
W2 Contractor
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🔒 - Security
Unknown
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📍 - Location detailed
Charlotte, NC
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🧠 - Skills detailed
#Data Lake #Automation #Scala #Big Data #SQL (Structured Query Language) #Programming #GCP (Google Cloud Platform) #PySpark #Python #Cloud #Data Science #Data Quality #Apache Spark #Code Reviews #Spark (Apache Spark) #Data Pipeline #Security #Data Security #AWS (Amazon Web Services) #Compliance #Computer Science #Azure #Data Engineering #DevOps #Data Processing
Role description
Dice is the leading career destination for tech experts at every stage of their careers. Our client, Innorev Technologies, Inc, is seeking the following. Apply via Dice today!
Role: Data Engineer (Python + Pyspark)
Onsite Role in Charlotte, NC
W2 Contract position
JD:
Key Responsibilities:
• Design, develop, and maintain scalable data pipelines using Spark/PySpark.
• Automate workflows and job scheduling using Autosys.
• Collaborate with data scientists, analysts, and other stakeholders to understand data requirements.
• Optimize data processing for performance and scalability.
• Ensure data quality, integrity, and governance across all pipelines.
• Monitor and troubleshoot production data pipelines and workflows.
• Participate in code reviews and contribute to best practices in data engineering.
Required Skills & Qualifications:
• 8 12 years of experience in data engineering or related roles.
• Strong hands-on experience with Apache Spark and PySpark.
• Proficiency in Autosys for job scheduling and workflow automation.
• Solid programming skills in Python and SQL.
• Experience with distributed data processing and big data technologies.
• Familiarity with cloud platforms (AWS, Azure, or Google Cloud Platform) is a plus.
• Strong problem-solving and communication skills.
• Bachelor s or Master s degree in Computer Science, Engineering, or a related field.
Preferred Qualifications:
• Experience with data lake architectures and data warehousing.
• Exposure to CI/CD pipelines and DevOps practices.
• Knowledge of data security and compliance standards.
Dice is the leading career destination for tech experts at every stage of their careers. Our client, Innorev Technologies, Inc, is seeking the following. Apply via Dice today!
Role: Data Engineer (Python + Pyspark)
Onsite Role in Charlotte, NC
W2 Contract position
JD:
Key Responsibilities:
• Design, develop, and maintain scalable data pipelines using Spark/PySpark.
• Automate workflows and job scheduling using Autosys.
• Collaborate with data scientists, analysts, and other stakeholders to understand data requirements.
• Optimize data processing for performance and scalability.
• Ensure data quality, integrity, and governance across all pipelines.
• Monitor and troubleshoot production data pipelines and workflows.
• Participate in code reviews and contribute to best practices in data engineering.
Required Skills & Qualifications:
• 8 12 years of experience in data engineering or related roles.
• Strong hands-on experience with Apache Spark and PySpark.
• Proficiency in Autosys for job scheduling and workflow automation.
• Solid programming skills in Python and SQL.
• Experience with distributed data processing and big data technologies.
• Familiarity with cloud platforms (AWS, Azure, or Google Cloud Platform) is a plus.
• Strong problem-solving and communication skills.
• Bachelor s or Master s degree in Computer Science, Engineering, or a related field.
Preferred Qualifications:
• Experience with data lake architectures and data warehousing.
• Exposure to CI/CD pipelines and DevOps practices.
• Knowledge of data security and compliance standards.






