Lead Data Engineer
Posted Today by Forsyth Barnes
£550 Per day
Outside
Hybrid
London Area, United Kingdom
Summary: The Lead Data Engineer will join a high-performing team to design and evolve a modern Databricks + AWS lakehouse architecture aimed at supporting financial institutions in combating fraud and financial crime. This hands-on leadership role involves building scalable data solutions and optimizing data pipelines while ensuring data quality and governance. The position requires collaboration with various teams to translate requirements into actionable insights from large datasets. The contract is for six months with a focus on delivering robust data platforms using modern cloud technologies.
Key Responsibilities:
- 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
Key Skills:
- 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
Salary (Rate): £550 daily
City: London
Country: United Kingdom
Working Arrangements: hybrid
IR35 Status: outside IR35
Seniority Level: Senior
Industry: IT
Lead Data Engineer (Contract)
Location: London (2 days onsite per week)
Day Rate : £500-£550 Per day (Outside IR35)
Duration: 6-month contract
Start: ASAP
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 + AWS 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