At a Glance
- Tasks: Lead the design and build of advanced data platforms for tackling financial crime.
- Company: Join a high-performing team in a dynamic London-based tech environment.
- Benefits: Competitive day rate, flexible work schedule, and opportunity for professional growth.
- Other info: Mentorship opportunities and a collaborative culture await you.
- Why this job: Make a real impact by delivering scalable data solutions using cutting-edge technologies.
- Qualifications: Strong experience in data engineering, Databricks, and cloud architectures required.
The predicted salary is between 39600 - 46200 € per year.
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.
Lead Data Engineer employer: Forsyth Barnes
Join a dynamic and innovative team in London as a Lead Data Engineer, where you'll have the opportunity to work on cutting-edge data platforms that combat fraud and financial crime. Our collaborative work culture fosters continuous learning and mentorship, ensuring that you grow alongside your peers while enjoying the flexibility of a hybrid work model. With competitive day rates and a focus on modern cloud technologies, this role offers a rewarding environment for those looking to make a significant impact in the financial sector.
StudySmarter Expert Advice🤫
We think this is how you could land Lead Data Engineer
✨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 referrals and insider info about job openings.
✨Show Off Your Skills
Don’t just talk about your experience; demonstrate it! Create a portfolio showcasing your projects, especially those involving Databricks, PySpark, or AWS. This gives potential employers a tangible sense of what you can do.
✨Ace the Interview
Prepare for technical interviews by brushing up on your data engineering skills. Be ready to discuss your past projects and how you tackled challenges. Practice common interview questions and think about how you can relate your experience to the job description.
✨Apply Through Our Website
We’ve got loads of opportunities waiting for you! Make sure to apply through our website for the best chance at landing that Lead Data Engineer role. It’s a great way to get noticed and show your enthusiasm for joining our team.
We think you need these skills to ace Lead Data Engineer
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, PySpark, and AWS, as well as any leadership roles you've held. 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 designed scalable data solutions or mentored engineers, and show us your passion for tackling financial crime.
Showcase Your Technical Skills:In your application, don't forget to showcase your technical skills. List your experience with data pipelines, orchestration tools, and CI/CD practices. We love seeing concrete examples of how you've implemented these in past roles!
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 get all the updates directly from us. Plus, it shows you're keen on joining our team!
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 require you to think on your feet. Be ready to discuss how you would design a scalable data solution or handle a data quality issue. Practising these scenarios can help you articulate your thought process clearly.
✨Communicate Effectively
Strong communication skills are key, especially when collaborating with non-technical teams. Practice explaining complex technical concepts in simple terms, so you can showcase your ability to bridge the gap between tech and business needs.
