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- Tasks: Lead the design and build of advanced data platforms for tackling financial crime.
- Company: Join a high-performing team in a dynamic financial tech environment.
- Benefits: Competitive day rate, flexible work schedule, and opportunity for professional growth.
- Other info: Hands-on leadership role with excellent mentorship opportunities.
- Why this job: Make a real impact by delivering scalable data solutions using cutting-edge technologies.
- Qualifications: Strong experience in data engineering, AWS, and building large-scale data pipelines.
Location: London (2 days onsite per week)
Day Rate: £525-550 Per day (Outside IR35)
Duration: min. 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
Lead Data Engineer SQL AWS in London employer: Forsyth Barnes
Contact Detail:
Forsyth Barnes Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Lead Data Engineer SQL AWS in London
✨Network Like a Pro
Get out there and connect with people in the industry! Attend meetups, webinars, or even just grab a coffee with someone who’s already in the role you want. Building relationships can lead to insider info on job openings and even referrals.
✨Show Off Your Skills
Don’t just talk about your experience; demonstrate it! Create a portfolio showcasing your projects, especially those involving Databricks, AWS, and data pipelines. This will give potential employers a clear view of what you can bring to the table.
✨Ace the Interview
Prepare for technical interviews by brushing up on your SQL, PySpark, and cloud architecture knowledge. Practice common interview questions and be ready to discuss your past projects in detail. Confidence is key!
✨Apply Through Our Website
When you find a job that fits, apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, we love seeing candidates who are proactive about their job search.
We think you need these skills to ace Lead Data Engineer SQL AWS in London
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to the Lead Data Engineer role. Highlight your experience with Databricks, AWS, and building scalable data pipelines. We want to see how your skills match what we're looking for!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you're the perfect fit for our team. Mention specific projects where you've led data solutions and how you’ve tackled challenges in the past.
Showcase Your Technical Skills: Don’t hold back on showcasing your technical expertise! Include details about your experience with PySpark, SQL, and cloud architectures. We love seeing hands-on experience, so be specific about your contributions.
Apply Through Our Website: We encourage you to apply through our website for a smoother process. It helps us keep track of applications and ensures you don’t miss out on any important updates from us!
How to prepare for a job interview at Forsyth Barnes
✨Know Your Tech Inside Out
Make sure you’re well-versed in Databricks, PySpark, SQL, and AWS. Brush up on your knowledge of data architectures and be ready to discuss how you've implemented them in past projects. This will show that you can hit the ground running.
✨Prepare for Scenario-Based Questions
Expect questions that ask you to solve real-world problems related to data pipelines and architecture. Think about specific challenges you've faced and how you overcame them. Use the STAR method (Situation, Task, Action, Result) to structure your answers.
✨Showcase Your Leadership Skills
As a Lead Data Engineer, you'll need to demonstrate your ability to mentor and guide others. Be prepared to share examples of how you've led teams, set engineering standards, and fostered collaboration across departments.
✨Understand the Business Context
Since this role involves supporting financial institutions, it’s crucial to understand the implications of data governance and compliance in this sector. Familiarise yourself with common challenges in tackling fraud and financial crime, and be ready to discuss how your work can contribute to these efforts.