At a Glance
- Tasks: Lead a team of Data Engineers while hands-on with data architecture and delivery.
- Company: Join a fast-growing RegTech SaaS provider shaping the future of compliance.
- Benefits: Enjoy private medical insurance, life insurance, flexible hours, and career progression.
- Other info: Inclusive culture with opportunities for personal and professional growth.
- Why this job: Make an impact by modernising data infrastructure for major financial institutions.
- Qualifications: Experience in leading teams and building data pipelines with Python and PySpark.
The predicted salary is between 80000 - 100000 £ per year.
Novatus Global is a Series B scale-up RegTech SaaS provider and boutique advisory firm, helping financial institutions manage their most complex regulatory requirements. Our flagship SaaS platform, En:ACT, is a market-leading solution for regulatory transaction reporting and reconciliation across global regimes. En:ACT automates reporting, reconciles data across systems, and maps errors directly to regulatory rules, helping firms remediate quickly, reduce risk, and meet regulatory obligations with confidence.
Alongside our SaaS offering, our unique model delivers consulting services across Risk & Compliance, ESG, Strategy, Data, and Operations. Backed by North American private equity investment, and partnerships with the London Stock Exchange Group and Snowflake’s global data platform, we are shaping the future of regulatory compliance through innovation in both advisory and technology.
As a Data Engineering Lead, you will manage a team of Data Engineers whilst remaining hands-on with delivery and architecture. You'll be providing technical leadership and mentorship to your team, and writing clean, maintainable, and well-tested code.
You will be accountable for our configuration-driven data platform in Databricks, enabling non-engineers to define regulatory logic, and our Snowflake data warehouse, ensuring scalability, auditability, and fitness for client-facing regulatory use cases. You will set technical direction, drive standards, and ensure high-quality execution across the team.
You’ll join at a pivotal stage as we modernize our data infrastructure, migrating from Python scripts and MySQL to Databricks and Snowflake. Our systems power regulatory reporting for major financial institutions, requiring precision, traceability, and reliability.
- Own the architecture, roadmap and delivery for our configuration-driven data framework in Databricks and our Snowflake warehouse.
- Manage and mentor a team of Data Engineers in a player/coach capacity.
- Design, build, and optimize data pipelines using Databricks, Kafka, Python and PySpark.
- Evolve a configuration-driven platform enabling non-engineers to define regulatory logic.
- Implement robust data quality controls including testing, validation, monitoring, and alerting.
- Drive performance optimization across Spark and Snowflake workloads.
- Partner with Product, Engineering, DevOps, and Regulatory teams to translate requirements into scalable technical designs.
- Improve engineering standards, processes, and tooling across the data function.
Experience required:
- Leading an Engineering team.
- Building data pipelines using Python and PySpark.
- Designing auditable, reproducible data pipelines in regulated or high-integrity environments.
- Writing and optimizing complex SQL queries on large data sets.
- Strong data modeling and warehouse design fundamentals.
- Strong software engineering fundamentals (clean code, automated testing, CI/CD, observability).
- Experience with modern cloud data platforms and orchestration tools.
- Translating complex regulatory requirements into technical specifications.
- Hands-on experience with AWS cloud infrastructure.
- Building new data platforms or modernizing legacy systems.
- FinTech, RegTech, or financial services background.
We offer:
- Private Medical Insurance (AXA) – includes mental health, dental, vision, and private GP access.
- Life Insurance (4× salary) with Unum.
- Unum’s Help@Hand: includes medical second opinions, physiotherapy, lifestyle coaching, savings and discounts, and cancer support services for you, your partner, and your child(ren).
- Employee Assistance Program.
- Enhanced parental leave (maternity & paternity).
- Accelerated career progression based on performance, not tenure.
- Holiday entitlement increases with tenure.
- Flexible hours with core collaboration time.
- Paid volunteering leave.
- Gym & fitness discounts.
- Quarterly socials, and office snacks & drinks.
All employment decisions are made based on business needs, role requirements, and individual qualifications, without regard to race, age, religion or belief, sex, sexual orientation, gender identity or expression, marital or civil partnership status, pregnancy or maternity, socioeconomic background, disability, or any other characteristic protected under the Equality Act 2010. We maintain a workplace culture that is inclusive, respectful, and supportive. This commitment is embedded in all aspects of our employment practices, including recruitment, compensation, professional development, promotion, and workplace conduct.
Data Engineering - Team Lead in City of London employer: Novatus
Contact Detail:
Novatus Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Engineering - Team Lead in City of London
✨Tip Number 1
Network like a pro! Reach out to your connections in the industry, attend meetups, and engage with professionals on LinkedIn. You never know who might have the inside scoop on job openings or can refer you directly.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those related to data engineering and compliance. 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 technical questions and scenarios relevant to the role. Practice explaining complex concepts in simple terms, as you'll need to communicate effectively with both technical and non-technical teams.
✨Tip Number 4
Don't forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, it shows you're genuinely interested in joining our team at Novatus Global.
We think you need these skills to ace Data Engineering - Team Lead in City of London
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to the Data Engineering Lead role. Highlight your experience with Databricks, Snowflake, and any relevant leadership roles. We want to see how your skills align with our needs!
Showcase Your Projects: Include specific projects where you've built data pipelines or led a team. We love seeing real examples of your work, especially if they relate to regulatory compliance or financial services.
Be Clear and Concise: When writing your application, keep it clear and to the point. Use bullet points for easy reading and make sure to highlight your key achievements. We appreciate straightforward communication!
Apply Through Our Website: Don’t forget to apply through our website! It’s the best way for us to receive your application and ensures you’re considered for the role. We can’t wait to hear from you!
How to prepare for a job interview at Novatus
✨Know Your Tech Stack
Make sure you’re well-versed in Databricks, Snowflake, Python, and PySpark. Brush up on your knowledge of data pipelines and how to optimise them, as you'll likely be asked about your hands-on experience with these technologies.
✨Showcase Leadership Skills
As a Data Engineering Lead, you’ll need to demonstrate your ability to manage and mentor a team. Prepare examples of how you've successfully led teams in the past, focusing on your approach to technical leadership and fostering collaboration.
✨Understand Regulatory Requirements
Familiarise yourself with the regulatory landscape relevant to financial institutions. Be ready to discuss how you can translate complex regulatory requirements into technical specifications, as this is crucial for the role.
✨Prepare for Problem-Solving Questions
Expect to tackle some technical challenges during the interview. Practice explaining your thought process when designing data architectures or optimising data workflows, as this will showcase your problem-solving skills and technical expertise.