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- Tasks: Lead the design and build of advanced data platforms for tackling fraud in finance.
- Company: Join a high-performing team at a leading financial tech company.
- Benefits: Competitive day rate, flexible work environment, and hands-on leadership experience.
- Other info: Mentorship opportunities and a dynamic, collaborative work culture.
- Why this job: Make a real impact by delivering scalable data solutions using cutting-edge cloud technologies.
- Qualifications: Strong experience in data engineering, Databricks, and AWS required.
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 (Ref: 196438) 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 (Ref: 196438) 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, or data pipelines. This gives potential employers a tangible sense of what you can do.
✨Ace the Interview
Prepare for technical interviews by brushing up on your knowledge of Spark, PySpark, and AWS. Practice common interview questions and be ready to discuss your past projects in detail. Confidence is key!
✨Apply Through Our Website
Make sure to apply directly through our website for the best chance at landing that Lead Data Engineer role. We love seeing candidates who take the initiative and show genuine interest in joining our team!
We think you need these skills to ace Lead Data Engineer (Ref: 196438) 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 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. Share specific examples of your past work that relate to the job description.
Showcase Your Technical Skills: Don’t hold back on showcasing your technical expertise! Mention your experience with Spark, PySpark, and any orchestration tools you've used. We love seeing hands-on experience in action.
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, and AWS. Brush up on your knowledge of data pipelines and cloud architectures, as you’ll likely be asked to discuss your hands-on experience with these technologies during the interview.
✨Showcase Your Leadership Skills
As a Lead Data Engineer, you’ll need to demonstrate your ability to mentor and guide others. Prepare examples of how you've led teams or projects in the past, focusing on your approach to problem-solving and setting engineering standards.
✨Prepare for Scenario-Based Questions
Expect questions that assess your ability to design scalable data solutions. Think through potential scenarios involving data governance, lineage, and compliance, and be ready to explain how you would tackle these challenges in a real-world context.
✨Communicate Clearly and Confidently
Strong communication skills are key for this role. Practice explaining complex technical concepts in simple terms, as you’ll need to collaborate with both technical and non-technical teams. Confidence in your delivery can make a big difference!