

Forsyth Barnes
Lead Data Engineer
⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for a Lead Data Engineer on a 6-month contract, based in London (2 days onsite weekly), offering £550 per day. Key skills include Databricks, PySpark, AWS, and data governance. Strong experience in building scalable data solutions is required.
🌎 - Country
United Kingdom
💱 - Currency
£ GBP
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💰 - Day rate
550
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🗓️ - Date
May 14, 2026
🕒 - Duration
More than 6 months
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🏝️ - Location
Hybrid
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📄 - Contract
Outside IR35
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🔒 - Security
Unknown
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📍 - Location detailed
London Area, United Kingdom
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🧠 - Skills detailed
#Monitoring #Data Science #S3 (Amazon Simple Storage Service) #Airflow #Spark SQL #Cloud #Data Pipeline #Spark (Apache Spark) #Data Governance #Leadership #PySpark #Data Quality #Compliance #Terraform #Python #SQL (Structured Query Language) #ML (Machine Learning) #Automated Testing #NiFi (Apache NiFi) #AWS (Amazon Web Services) #Scala #Databricks #Data Architecture #Datasets #IAM (Identity and Access Management) #Observability #Apache NiFi #Data Ingestion #Data Processing #Lambda (AWS Lambda) #Infrastructure as Code (IaC) #Data Engineering #Batch
Role description
Lead Data Engineer (Contract)
Location: London (2 days onsite per week)
Day Rate: £550 Per day (Outside IR35)
Duration: min. 6-month contract
Start: ASAP
Contact: Matthew.Makranczy@forsythbarnes.com
Overview
We are looking for a Lead Data Engineer to join a high-performing team delivering advanced data platforms that support financial institutions in tackling fraud and financial crime.
In this role, you will help design and evolve a modern Databricks + lakehouse architecture, enabling analytics, machine learning, and investigative teams to generate actionable insights from large-scale datasets.
This is a hands-on leadership position focused on building robust, scalable, and governed data solutions using modern cloud technologies.
The Role
• Own the end-to-end design, build, optimisation, and support of scalable Spark / PySpark data pipelines (batch and streaming)
• Define and implement lakehouse architecture standards (medallion model: bronze, silver, gold), including governance, lineage, and data quality controls
• Design and manage secure data ingestion frameworks (e.g. Apache NiFi, APIs, SFTP/FTPS) for internal and external data sources
• Architect and maintain secure AWS-based data infrastructure (S3, IAM, KMS, Glue, Lake Formation, Lambda, Step Functions, CloudWatch, etc.)
• Implement orchestration using tools such as Airflow, Databricks Workflows, and Step Functions
• Champion data quality, observability, and reliability (SLAs, monitoring, alerting, reconciliation)
• Drive CI/CD best practices for data platforms (infrastructure as code, automated testing, versioning, environment promotion)
• Mentor engineers on distributed data processing, performance optimisation, and cost efficiency
• Collaborate with data science, product, and compliance teams to translate requirements into scalable data solutions
Required Skills & Experience
• Strong experience as a Senior or Lead Data Engineer with ownership of end-to-end data solutions
• Expertise in Databricks, PySpark / Spark, SQL, and Python
• Proven experience building and optimising large-scale data pipelines in production environments
• Strong knowledge of cloud data architectures, particularly within AWS
• Experience designing scalable data models and reusable frameworks
• Hands-on experience with orchestration tools such as Airflow or similar
• Solid understanding of data governance, lineage, and compliance requirements
• Experience with CI/CD pipelines and infrastructure as code (e.g. Terraform, CloudFormation)
• Strong communication skills with the ability to collaborate across technical and non-technical teams
What We’re Looking For
• A hands-on technical leader who can design, build, and deliver solutions independently
• Someone comfortable working with high-volume, high-throughput data systems
• Strong problem-solving skills and a pragmatic, delivery-focused mindset
• Experience mentoring engineers and setting engineering standards and best practices
• Ability to balance technical excellence with delivery timelines
Lead Data Engineer (Contract)
Location: London (2 days onsite per week)
Day Rate: £550 Per day (Outside IR35)
Duration: min. 6-month contract
Start: ASAP
Contact: Matthew.Makranczy@forsythbarnes.com
Overview
We are looking for a Lead Data Engineer to join a high-performing team delivering advanced data platforms that support financial institutions in tackling fraud and financial crime.
In this role, you will help design and evolve a modern Databricks + lakehouse architecture, enabling analytics, machine learning, and investigative teams to generate actionable insights from large-scale datasets.
This is a hands-on leadership position focused on building robust, scalable, and governed data solutions using modern cloud technologies.
The Role
• Own the end-to-end design, build, optimisation, and support of scalable Spark / PySpark data pipelines (batch and streaming)
• Define and implement lakehouse architecture standards (medallion model: bronze, silver, gold), including governance, lineage, and data quality controls
• Design and manage secure data ingestion frameworks (e.g. Apache NiFi, APIs, SFTP/FTPS) for internal and external data sources
• Architect and maintain secure AWS-based data infrastructure (S3, IAM, KMS, Glue, Lake Formation, Lambda, Step Functions, CloudWatch, etc.)
• Implement orchestration using tools such as Airflow, Databricks Workflows, and Step Functions
• Champion data quality, observability, and reliability (SLAs, monitoring, alerting, reconciliation)
• Drive CI/CD best practices for data platforms (infrastructure as code, automated testing, versioning, environment promotion)
• Mentor engineers on distributed data processing, performance optimisation, and cost efficiency
• Collaborate with data science, product, and compliance teams to translate requirements into scalable data solutions
Required Skills & Experience
• Strong experience as a Senior or Lead Data Engineer with ownership of end-to-end data solutions
• Expertise in Databricks, PySpark / Spark, SQL, and Python
• Proven experience building and optimising large-scale data pipelines in production environments
• Strong knowledge of cloud data architectures, particularly within AWS
• Experience designing scalable data models and reusable frameworks
• Hands-on experience with orchestration tools such as Airflow or similar
• Solid understanding of data governance, lineage, and compliance requirements
• Experience with CI/CD pipelines and infrastructure as code (e.g. Terraform, CloudFormation)
• Strong communication skills with the ability to collaborate across technical and non-technical teams
What We’re Looking For
• A hands-on technical leader who can design, build, and deliver solutions independently
• Someone comfortable working with high-volume, high-throughput data systems
• Strong problem-solving skills and a pragmatic, delivery-focused mindset
• Experience mentoring engineers and setting engineering standards and best practices
• Ability to balance technical excellence with delivery timelines






