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- Tasks: Lead architectural strategy and execution across multiple data engineering teams.
- Company: Accelerant, a fast-growing tech company focused on innovation.
- Benefits: Competitive salary, collaborative culture, and opportunities to work with cutting-edge AI technologies.
- Why this job: Shape the future of data engineering while driving AI transformation and operational excellence.
- Qualifications: 8-12+ years in data pipeline design, strong experience with Snowflake and cloud platforms.
- Other info: Join a dynamic team where your impact is felt across multiple product areas.
The predicted salary is between 72000 - 108000 £ per year.
Accelerant is seeking a Product Area Lead Architect to provide hands-on, operational architectural leadership across 5–6 autonomous product teams in the Data Ingestion & Egress product area. You will be accountable for ensuring architectural coherence, technical health, and effective cross-team execution - bridging high-level architectural strategy with sprint-level delivery. You will work closely with team architects, the senior leadership team, engineering managers, and product managers. This is not an ivory-tower architecture role. It is highly collaborative, pragmatic, and operational-focused on identifying architectural gaps, managing dependencies, and enabling teams to execute confidently within a shared architectural framework.
Key Responsibilities:
- Operational Architectural Leadership
- Ensure architectural alignment across 5–6 product teams, partnering closely with team architects and the Lead Data Architect.
- Proactively identify architectural gaps, technical debt, and quality risks; drive resolution through collaboration and influence.
- Manage cross-team technical dependencies to enable independent, parallel execution.
- Translate architectural strategy into clear, actionable guidance that teams can apply sprint-by-sprint.
- Maintain visibility into architectural health through reviews, metrics, and direct engagement.
- Cross-Team Coordination & Alignment
- Facilitate architectural discussions and decisions that span multiple teams.
- Resolve technical conflicts and competing approaches through principled, pragmatic decision-making.
- Ensure architectural decisions are clearly communicated, understood, and consistently applied.
- Act as an escalation point for complex cross-team technical challenges.
- Partner closely with frontend and consumer teams to ensure backend APIs and data services are intuitive, performant, and aligned with product needs.
- Design and Innovation
- Lead design of data pipeline architecture with focus on scalability, security, performance, and observability.
- Introduce innovative practices and technologies within the data engineering stack.
- Champion modern approaches to handling semi-structured data, metadata-driven pipelines, and real-time data streaming.
- Design and evolve high-performance, scalable backend services that support data ingestion, egress, and downstream consumers.
- Architect and guide implementation of distributed systems with a focus on reliability, fault tolerance, throughput, and latency.
- AI Transformation & Productivity Leadership
- Scale AI-driven development workflows across 5-6 data engineering teams, ensuring engineers leverage AI coding tools effectively for pipeline development, testing, and optimization.
- Guide team architects and coach senior engineers on effectively using AI tools to enhance productivity, code quality, and problem-solving approaches in their daily work.
- Establish metrics and feedback loops to measure the impact of AI on data engineering productivity and pipeline quality across AI providers and AI-tooling being used.
- Drive AI-enhanced capabilities such as automated pattern recognition, data quality validation, and pipeline optimization across the product area.
- Work hands-on with teams to identify opportunities for AI to solve operational challenges and improve velocity.
- Solution Evaluation & Quality Assurance
- Evaluate and recommend new data technologies and tools (Snowflake, dbt, streaming platforms) to enhance data engineering capabilities.
- Ensure architectural integrity and compliance with quality standards through code reviews, architectural assessments, and continuous monitoring.
- Proactively identify technical risks and devise strategies to ensure reliability, security, and performance of data pipelines.
Technical Requirements & Qualifications:
- 8–12+ years designing and operating modern data pipelines at scale.
- Strong hands-on experience with Snowflake, dbt, and cloud-native platforms (AWS preferred).
- Solid understanding of batch and real-time ingestion patterns.
- Proven experience architecting and running data platforms in production cloud environments.
- Experience with data orchestration, CI/CD for data systems, and DataOps practices.
- Familiarity with metadata-driven architectures and data observability frameworks.
- Deep experience designing and evolving well-structured APIs for data ingestion, egress, and platform integrations.
- Strong Python proficiency for data pipelines, backend services, and APIs in production.
- Proficient in handling JSON, XML, flat files, and other semi-structured formats.
- Strong understanding of data quality, schema evolution, pipeline resilience, and operational robustness.
- Deep knowledge of data architecture principles and design patterns.
- Proven experience designing and operating distributed systems in production.
- Strong ability to make pragmatic architectural tradeoffs across consistency, availability, performance, and scalability.
- Demonstrated ability to bridge long-term architectural vision with day-to-day execution.
- Hands-on experience using AI coding tools (GitHub Copilot, Cursor, Claude, etc.) in data engineering contexts.
- Understanding of AI-driven pipeline optimization, data quality improvement, and productivity gains.
- Proven ability to drive AI adoption and transformation across engineering teams.
- Proven experience operating across multiple agile teams in an architectural leadership role.
- Strong track record managing cross-team dependencies and resolving complex technical challenges.
- Excellent communication, facilitation, and influence skills across distributed teams.
- Strong problem-solving ability with a pragmatic, operational mindset.
Why Accelerant:
- Be the operational backbone ensuring architectural excellence across 5-6 data engineering teams.
- Drive day-to-day architectural alignment and resolve complex cross-team dependencies.
- Lead AI transformation and productivity improvements across multiple teams in real-time.
- Work hands-on with teams sprint-by-sprint to bridge strategy and execution.
- Shape how a fast-growing engineering organization maintains architectural consistency at scale.
- Work with cutting-edge AI technologies and data platform tools.
- Be part of a collaborative, innovative culture focused on operational excellence.
Lead Architect in London employer: Accelerant
Contact Detail:
Accelerant Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Lead Architect in London
✨Tip Number 1
Network like a pro! Reach out to folks in your industry on LinkedIn or at meetups. A friendly chat can lead to opportunities that aren’t even advertised yet.
✨Tip Number 2
Show off your skills! Create a portfolio or GitHub repo showcasing your projects and contributions. This gives potential employers a taste of what you can do beyond the CV.
✨Tip Number 3
Prepare for interviews by practising common questions and scenarios related to architectural leadership. We recommend doing mock interviews with friends or using online platforms to get comfortable.
✨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, we love seeing candidates who are proactive!
We think you need these skills to ace Lead Architect in London
Some tips for your application 🫡
Tailor Your Application: Make sure to customise your CV and cover letter for the Lead Architect role. Highlight your experience with data pipelines, architectural leadership, and any hands-on work with AI tools. We want to see how your skills align with our needs!
Showcase Collaboration Skills: Since this role is all about teamwork, emphasise your collaborative experiences. Share examples of how you've worked with cross-functional teams to resolve technical challenges or drive architectural decisions. We love a good team player!
Be Pragmatic and Clear: When describing your past projects, focus on practical solutions and clear outcomes. We appreciate straightforward communication, so make sure your application reflects that. Avoid jargon unless it’s necessary to convey your expertise.
Apply Through Our Website: Don’t forget to submit your application through our website! It’s the best way for us to keep track of your application and ensure it gets the attention it deserves. We can’t wait to hear from you!
How to prepare for a job interview at Accelerant
✨Know Your Architecture Inside Out
Make sure you have a solid understanding of architectural principles, especially in data pipelines. Be ready to discuss your past experiences with Snowflake, dbt, and cloud-native platforms like AWS. This will show that you can bridge high-level strategy with practical execution.
✨Showcase Your Collaboration Skills
Since this role is highly collaborative, prepare examples of how you've worked with cross-functional teams in the past. Highlight your ability to resolve conflicts and make principled decisions that benefit multiple teams. This will demonstrate your fit for the operational-focused nature of the role.
✨Be Ready to Discuss AI Integration
With AI being a key part of this position, come prepared to talk about your experience using AI coding tools and how you've leveraged them to enhance productivity. Share specific examples of how you've driven AI adoption within teams to solve operational challenges.
✨Prepare for Technical Deep Dives
Expect to dive deep into technical discussions during the interview. Brush up on your knowledge of data quality, schema evolution, and distributed systems. Being able to articulate your thought process and decision-making will be crucial in showcasing your expertise.
