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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 hands-on leadership experience.
- Other info: Opportunity to mentor and collaborate with diverse teams in a fast-paced setting.
- Why this job: Make a real impact by enabling analytics and machine learning on large datasets.
- Qualifications: Experience in data engineering, cloud technologies, and team leadership.
The predicted salary is between 126000 - 126000 £ per year.
Location: London (2 days onsite per week)
Day Rate: £525 Per day (Outside IR35)
Duration: 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
Lead Data Engineer (Ref: 196438) 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)
✨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
Get your hands dirty with practical projects. Showcase your skills by working on personal or open-source projects that demonstrate your expertise in Spark, AWS, and data pipelines. This not only boosts your portfolio but also gives you real-world examples to discuss in interviews.
✨Tip Number 3
Prepare for technical interviews by brushing up on key concepts related to lakehouse architecture and data governance. Practice explaining your thought process while solving problems, as this will show potential employers your leadership and analytical skills.
✨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 hiring process. Plus, it’s super easy to keep track of your applications!
We think you need these skills to ace Lead Data Engineer (Ref: 196438)
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 pipeline optimisation. 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 tackling fraud and financial crime through data engineering. Let us know how you can contribute to our high-performing team.
Showcase Your Projects: If you've worked on relevant projects, don’t hold back! Share specific examples of your work with Spark, PySpark, or any cloud technologies. We love seeing real-world applications of your skills.
Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, it’s super easy!
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, especially Databricks, AWS, and Spark/PySpark. Brush up on your knowledge of lakehouse architecture and be ready to discuss how you’ve implemented similar solutions in the past.
✨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, focusing on your approach to problem-solving and collaboration with cross-functional teams.
✨Prepare for Scenario-Based Questions
Expect questions that ask you to solve real-world problems related to data pipelines and architecture. Think through scenarios where you had to optimise performance or ensure data quality, and be ready to explain your thought process and the outcomes.
✨Ask Insightful Questions
At the end of the interview, don’t forget to ask questions that show your interest in the role and the company. Inquire about their current data challenges, team dynamics, or future projects. This not only shows your enthusiasm but also helps you gauge if it’s the right fit for you.