Lead Architect

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, 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.

• 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

• 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

• 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

• 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.

• 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.

• 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 Data Ops practices
• Familiarity with…