Lead Engineer/Data Engineer
City of London, Greater London
£550/day
Posted 1 day ago
About the role
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
About this listing
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