Lead Data Engineer (Contract)
Location: London (2 days onsite per week)
Day Rate: £525-550 Per day (Outside IR35)
Duration: min. 6-month contract
Start: ASAP
Contact:
While professional experience and qualifications are key for this role, make sure to check you have the preferable soft skills before applying if required.
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 xwzovoh 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