Data Engineering - Team Lead in City of London

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 leading an Engineering team. Experience building data pipelines using Python and PySpark. Experience designing auditable, reproducible data pipelines in regulated or high-integrity environments. Able to write and optimize 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. Ability to translate complex regulatory requirements into technical specifications. Hands-on experience with AWS cloud infrastructure. Experience building new data platforms or modernizing legacy systems. FinTech, RegTech, or financial services background.

We offer Private Medical Insurance, Life Insurance, Employee Assistance Program, Enhanced parental leave, Accelerated career progression based on performance, Holiday entitlement increases with tenure, Flexible hours with core collaboration time, Paid volunteering leave, Gym & fitness discounts, and Quarterly socials.

All employment decisions are made based on business needs, role requirements, and individual qualifications, without regard to any characteristic protected under the Equality Act 2010. We maintain a workplace culture that is inclusive, respectful, and supportive.