

G MASS Consulting
Data Engineer (FinTech)
⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for a Data Engineer (FinTech) on an initial 6-month contract, focusing on scalable data solutions. Requires strong SQL, Apache Spark, and Python skills; experience in financial services; and familiarity with cloud platforms. Salary negotiable.
🌎 - Country
United Kingdom
💱 - Currency
£ GBP
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💰 - Day rate
Unknown
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🗓️ - Date
February 4, 2026
🕒 - Duration
More than 6 months
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🏝️ - Location
Unknown
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📄 - Contract
Unknown
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🔒 - Security
Unknown
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📍 - Location detailed
London, England, United Kingdom
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🧠 - Skills detailed
#GIT #Big Data #Apache Spark #Python #Data Quality #Qlik #AWS (Amazon Web Services) #Jupyter #AI (Artificial Intelligence) #Tableau #Data Pipeline #Data Engineering #BI (Business Intelligence) #Java #Data Processing #Data Manipulation #GitHub #Datasets #DevOps #SQL (Structured Query Language) #GCP (Google Cloud Platform) #Spark (Apache Spark) #Version Control #BitBucket #"ETL (Extract #Transform #Load)" #Data Ingestion #Data Extraction #Azure #SQL Queries #Microsoft Power BI #PySpark #Documentation #Scala #Azure DevOps #Cloud #Storage #Data Science #Data Visualisation
Role description
G MASS is partnering with a global FinTech business to support the build-out of a next-generation data engineering capability within a large-scale enterprise data environment. This role sits within a highly technical engineering team focused on delivering AI-enabled, cloud-native data products used across the business.
You'll join a collaborative engineering function responsible for designing and delivering robust, scalable data solutions. The work spans data ingestion, transformation, analytics and enablement, supporting both internal stakeholders and client-facing products.
Key responsibilities
• Design, develop and maintain scalable data pipelines for ingestion, transformation and storage
• Write efficient SQL queries to support data extraction, manipulation and analysis
• Use Apache Spark and Python to process large datasets and automate workflows
• Partner with data scientists, engineers and business stakeholders to translate requirements into data solutions
• Implement data quality checks and validation to ensure accuracy and reliability
• Analyse complex datasets to identify trends, patterns and anomalies
• Produce and maintain clear documentation covering data processes and architecture
• Support stakeholders with data visualisation and interpretation of outputs
Requirements
• Strong experience in SQL for data manipulation and analysis
• Hands-on experience with Apache Spark (Java, SQL or PySpark) and Python
• Experience working with large, complex datasets in enterprise environments
• Exposure to cloud data platforms (AWS, Azure or GCP) and big data technologies
• Confident communicator, comfortable working across technical and non-technical teams
• Background or exposure to financial services or capital markets
Nice to have
• Experience using Java in data processing or integration contexts
• Knowledge of ETL processes and data warehousing concepts
• Experience with data visualisation tools (Power BI, Tableau, Qlik)
• Familiarity with data science notebooks (e.g. Jupyter, Zeppelin)
• Version control experience (Git, GitHub, Bitbucket, Azure DevOps)
Benefits
Initial 6-month contract, with strong possibility of extension and/or permanency.
Salary to be discussed.
G MASS is partnering with a global FinTech business to support the build-out of a next-generation data engineering capability within a large-scale enterprise data environment. This role sits within a highly technical engineering team focused on delivering AI-enabled, cloud-native data products used across the business.
You'll join a collaborative engineering function responsible for designing and delivering robust, scalable data solutions. The work spans data ingestion, transformation, analytics and enablement, supporting both internal stakeholders and client-facing products.
Key responsibilities
• Design, develop and maintain scalable data pipelines for ingestion, transformation and storage
• Write efficient SQL queries to support data extraction, manipulation and analysis
• Use Apache Spark and Python to process large datasets and automate workflows
• Partner with data scientists, engineers and business stakeholders to translate requirements into data solutions
• Implement data quality checks and validation to ensure accuracy and reliability
• Analyse complex datasets to identify trends, patterns and anomalies
• Produce and maintain clear documentation covering data processes and architecture
• Support stakeholders with data visualisation and interpretation of outputs
Requirements
• Strong experience in SQL for data manipulation and analysis
• Hands-on experience with Apache Spark (Java, SQL or PySpark) and Python
• Experience working with large, complex datasets in enterprise environments
• Exposure to cloud data platforms (AWS, Azure or GCP) and big data technologies
• Confident communicator, comfortable working across technical and non-technical teams
• Background or exposure to financial services or capital markets
Nice to have
• Experience using Java in data processing or integration contexts
• Knowledge of ETL processes and data warehousing concepts
• Experience with data visualisation tools (Power BI, Tableau, Qlik)
• Familiarity with data science notebooks (e.g. Jupyter, Zeppelin)
• Version control experience (Git, GitHub, Bitbucket, Azure DevOps)
Benefits
Initial 6-month contract, with strong possibility of extension and/or permanency.
Salary to be discussed.






