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 financial tech environment.
- Benefits: Competitive day rate, flexible work schedule, and hands-on leadership experience.
- Other info: Opportunity for professional growth and mentorship in a collaborative setting.
- Why this job: Make a real impact by driving innovative data solutions in a crucial industry.
- Qualifications: Experience in data engineering, cloud technologies, and team leadership.
The predicted salary is between 132000 - 132000 € 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.
Lead Data Engineer employer: Forsyth Barnes
As a Lead Data Engineer at our London-based firm, you will be part of a dynamic and innovative team dedicated to combating financial crime through advanced data solutions. We pride ourselves on fostering a collaborative work culture that encourages professional growth and offers competitive day rates, alongside the flexibility of hybrid working arrangements. Join us to make a meaningful impact while developing your skills in a cutting-edge environment that values creativity and excellence.
StudySmarter Expert Advice🤫
We think this is how you could land Lead Data Engineer
✨Tip Number 1
Network like a pro! Reach out to your connections in the data engineering field and let them know you're on the hunt for a Lead Data Engineer role. You never know who might have the inside scoop on an opportunity or can refer you directly.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your past projects, especially those involving Spark, PySpark, and cloud technologies. This will give potential employers a taste of what you can bring to the table.
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge and soft skills. Be ready to discuss your experience with lakehouse architecture and data governance, as well as how you’ve mentored others in the past.
✨Tip Number 4
Don’t forget to apply through our website! We’ve got some fantastic opportunities waiting for you, and applying directly can sometimes give you a leg up in the process. Let’s get you that Lead Data Engineer position!
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, Spark, and AWS, as well as any leadership roles you've held. We want to see how your skills align with 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 passionate about data engineering and how you can contribute to our team. Be sure to mention specific projects or experiences that relate to the job description.
Showcase Your Technical Skills:In your application, don't forget to showcase your technical skills. Mention your experience with data pipelines, lakehouse architecture, and any tools like Airflow or Apache NiFi. We love seeing concrete examples of your work!
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 the best chance to join our high-performing team. Let's make it happen!
How to prepare for a job interview at Forsyth Barnes
✨Know Your Tech Stack
Make sure you’re well-versed in the technologies mentioned in the job description, like Databricks, Spark, and AWS services. Brush up on your knowledge of data pipelines and lakehouse architecture, as these will likely be key discussion points 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 successfully led projects or teams in the past, focusing on your hands-on approach and how you’ve driven best practices in data engineering.
✨Prepare for Scenario-Based Questions
Expect questions that ask you to solve real-world problems related to data ingestion, governance, and quality controls. Think through scenarios where you had to design or optimise data solutions, and be ready to explain your thought process and decisions.
✨Ask Insightful Questions
Interviews are a two-way street! Prepare thoughtful questions about the team’s current challenges, the company’s data strategy, and how they measure success in their data initiatives. This shows your genuine interest and helps you assess if the role is the right fit for you.
