Data Engineer (Python / PySpark / Data Pipelines / Big Data)
⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for a Data Engineer (Python/PySpark/Data Pipelines/Big Data) in Glasgow, hybrid, with a contract length of "unknown" and a pay rate of "unknown." Key skills include Python, PySpark, SQL, and Core Java.
🌎 - Country
United Kingdom
💱 - Currency
£ GBP
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💰 - Day rate
360
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🗓️ - Date discovered
September 3, 2025
🕒 - Project duration
Unknown
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🏝️ - Location type
Hybrid
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📄 - Contract type
Unknown
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🔒 - Security clearance
Unknown
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📍 - Location detailed
Glasgow, Scotland, United Kingdom
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🧠 - Skills detailed
#Data Architecture #BitBucket #Data Lake #Security #AWS (Amazon Web Services) #Java #Data Warehouse #PySpark #Spark (Apache Spark) #SQL (Structured Query Language) #GIT #Version Control #GitLab #Data Engineering #Data Pipeline #Python #Big Data
Role description
We are hiring for Data Engineer (Python / PySpark / Data pipelines / Big Data)
Location : Glasgow - Hybrid
• Strong experience with Python, PySpark, and SQL.
• Build and maintain robust data architectures and pipelines to ensure durable, complete, and consistent data transfer and processing.
• Proficiency in Core Java, including Collections, Concurrency, and Memory Management.
• Design and implement data warehouses and data lakes that can handle large volumes of data and meet all security requirements.
• A solid background in performance tuning, profiling, and resolving production issues in distributed systems.
• Experience with version control systems like Git, GitLab, or Bitbucket & AWS is a plus.
Key Skills : Data architectures / Data pipelines / data warehouses / data lakes / Python / PySpark
We are hiring for Data Engineer (Python / PySpark / Data pipelines / Big Data)
Location : Glasgow - Hybrid
• Strong experience with Python, PySpark, and SQL.
• Build and maintain robust data architectures and pipelines to ensure durable, complete, and consistent data transfer and processing.
• Proficiency in Core Java, including Collections, Concurrency, and Memory Management.
• Design and implement data warehouses and data lakes that can handle large volumes of data and meet all security requirements.
• A solid background in performance tuning, profiling, and resolving production issues in distributed systems.
• Experience with version control systems like Git, GitLab, or Bitbucket & AWS is a plus.
Key Skills : Data architectures / Data pipelines / data warehouses / data lakes / Python / PySpark
