Data Engineer
⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is a Data Engineer contract in London for 6 months (Outside IR35), requiring strong Python, PySpark, SQL, and cloud data tools experience. Familiarity with commodities trading and data integration is preferred. On-site work is required 4 days a week.
🌎 - Country
United Kingdom
💱 - Currency
£ GBP
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💰 - Day rate
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🗓️ - Date discovered
June 18, 2025
🕒 - Project duration
More than 6 months
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🏝️ - Location type
On-site
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📄 - Contract type
Outside IR35
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🔒 - Security clearance
Unknown
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📍 - Location detailed
London Area, United Kingdom
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🧠 - Skills detailed
#Debugging #Data Quality #Scala #Cloud #Azure #Visualization #GIT #Data Lake #ADF (Azure Data Factory) #Spark (Apache Spark) #SQL (Structured Query Language) #Data Integration #Data Engineering #Data Science #"ETL (Extract #Transform #Load)" #Data Pipeline #Azure Data Factory #Synapse #Python #Pandas #Databricks #PySpark
Role description
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Data Engineer
Location: London (4 days/week on-site)
Type: Contract (Outside IR35)
Duration: 6 months
A leading physical commodities trading firm is seeking a Data Engineer for a 6-month contract (Outside IR35). You’ll work on-site in London 4 days per week, building and optimizing data pipelines in a fast-paced, data-driven trading environment.
Responsibilities:
• Build and maintain scalable data pipelines (ETL/ELT)
• Support data users with ingestion, debugging, and navigation
• Integrate data from diverse sources (structured & unstructured)
• Monitor and ensure data quality
• Maintain and improve existing production processes
• Develop dashboards and visualizations
• Work closely with data scientists and stakeholders
• Follow CI/CD and code best practices (Git, testing, reviews)
Tech Stack & Experience:
• Strong Python (Pandas), PySpark, and SQL skills
• Cloud data tools (Azure Data Factory, Synapse, Databricks, etc.)
• Data integration experience across formats and platforms
• Strong communication and data literacy
Nice to Have:
• Commodities/trading background
• Experience with data lakes and open-source data tools
• Familiarity with governance frameworks (OPA, Ranger)
