Lorien
Data Engineer
⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for a Data Engineer with active SC Clearance, offering a 6-month hybrid contract. Key skills include Azure Databricks, SQL, Python, and Spark. Experience in CI/CD and cloud-native design is essential, with a focus on data transformation in the financial sector.
🌎 - Country
United Kingdom
💱 - Currency
£ GBP
-
💰 - Day rate
Unknown
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🗓️ - Date
April 14, 2026
🕒 - Duration
More than 6 months
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🏝️ - Location
Hybrid
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📄 - Contract
Fixed Term
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🔒 - Security
Yes
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📍 - Location detailed
London Area, United Kingdom
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🧠 - Skills detailed
#Leadership #"ETL (Extract #Transform #Load)" #Azure Databricks #Agile #Cloudera #Data Quality #Scripting #Azure #Data Architecture #Migration #Data Engineering #PySpark #Cloud #Azure ADLS (Azure Data Lake Storage) #Unix #Spark (Apache Spark) #Metadata #ADF (Azure Data Factory) #Data Strategy #Azure Data Factory #SQL (Structured Query Language) #Observability #Data Lake #Strategy #DevOps #Linux #Shell Scripting #Storage #Apache Airflow #Python #Data Pipeline #Delta Lake #ADLS (Azure Data Lake Storage) #GitHub #Databricks #Data Management #Azure DevOps #Scala #Airflow
Role description
Data Engineer - SC Cleared
6 Month Contract
Hybrid - 2 days per week onsite
Please note: Active SC Clearance is required for this role
A leading organisation within the UK financial sector is embarking on a major data transformation programme. They are looking for an experienced Data Engineer to help design and deliver a modern, cloud‑first data platform that will underpin some of the organisation’s most critical functions.
Responsibilities:
• Design, build and deploy scalable, secure data solutions using Azure Databricks, Data Factory and Data Lake Storage.
• Develop and optimise advanced data pipelines with Python, SQL, Spark/PySpark and Delta Lake.
• Champion strong data quality, governance and observability practices.
• Modernise legacy systems and support large-scale migrations into Azure.
• Provide technical leadership, set engineering standards and contribute to architectural decisions.
• Mentor engineers and foster a culture of continuous improvement.
• Work closely with architecture, analytics and business teams to align engineering solutions with organisational needs.
Minimum Criteria
• Extensive experience with Azure services including Azure Databricks, Azure Data Lake Storage, and Azure Data Factory.
• Advanced proficiency in SQL, Python, and Spark (PySpark), with a strong focus on performance optimization and distributed processing.
• Proven experience in CI/CD practices using industry-standard tools (e.g., GitHub Actions, Azure DevOps).
• Strong understanding of data architecture principles and cloud-native design patterns.
Essential Criteria
• Demonstrated ability to lead technical delivery, mentor engineering teams and collaborate with stakeholders to ensure alignment between data solutions and business strategy.
• Proficiency in Linux/Unix environments and shell scripting.
• Deep understanding of source control, testing strategies, and agile development practices.
• Self-motivated with a strategic mindset and a passion for driving innovation in data engineering.
Desirable Criteria
• Experience delivering data pipelines on Hortonworks/Cloudera on-prem and leading cloud migration initiatives.
• Familiarity with Apache Airflow, data modelling, and metadata management
• Experience influencing enterprise data strategy and contributing to architectural governance.
To apply for this position please submit your CV.
Data Engineer - SC Cleared
6 Month Contract
Hybrid - 2 days per week onsite
Please note: Active SC Clearance is required for this role
A leading organisation within the UK financial sector is embarking on a major data transformation programme. They are looking for an experienced Data Engineer to help design and deliver a modern, cloud‑first data platform that will underpin some of the organisation’s most critical functions.
Responsibilities:
• Design, build and deploy scalable, secure data solutions using Azure Databricks, Data Factory and Data Lake Storage.
• Develop and optimise advanced data pipelines with Python, SQL, Spark/PySpark and Delta Lake.
• Champion strong data quality, governance and observability practices.
• Modernise legacy systems and support large-scale migrations into Azure.
• Provide technical leadership, set engineering standards and contribute to architectural decisions.
• Mentor engineers and foster a culture of continuous improvement.
• Work closely with architecture, analytics and business teams to align engineering solutions with organisational needs.
Minimum Criteria
• Extensive experience with Azure services including Azure Databricks, Azure Data Lake Storage, and Azure Data Factory.
• Advanced proficiency in SQL, Python, and Spark (PySpark), with a strong focus on performance optimization and distributed processing.
• Proven experience in CI/CD practices using industry-standard tools (e.g., GitHub Actions, Azure DevOps).
• Strong understanding of data architecture principles and cloud-native design patterns.
Essential Criteria
• Demonstrated ability to lead technical delivery, mentor engineering teams and collaborate with stakeholders to ensure alignment between data solutions and business strategy.
• Proficiency in Linux/Unix environments and shell scripting.
• Deep understanding of source control, testing strategies, and agile development practices.
• Self-motivated with a strategic mindset and a passion for driving innovation in data engineering.
Desirable Criteria
• Experience delivering data pipelines on Hortonworks/Cloudera on-prem and leading cloud migration initiatives.
• Familiarity with Apache Airflow, data modelling, and metadata management
• Experience influencing enterprise data strategy and contributing to architectural governance.
To apply for this position please submit your CV.
