Lead Full Stack Engineer
About Us
Fivetran and dbt Labs are bringing together two industry-leading companies with a shared mission: helping organizations unlock the full value of their data.
Together, we’re delivering the data infrastructure layer that helps organizations move, transform, and trust their data — from the moment data moves, through every transformation, to the context teams and AI systems rely on.
Fivetran helps organizations automate data movement across the systems, clouds, engines, and tools they rely on. dbt Labs pioneered analytics engineering, helping teams transform data into reliable, governed insights. Together, we support thousands of organizations as they build a trusted foundation for analytics, AI, and better business decisions.
As we bring our teams and technology together, we’re building on the strengths of both companies while continuing to deliver the products and experiences our customers know and trust. It’s an exciting time to join us: we’re creating a company with the scale, talent, and technology to help more organizations put their data to work with greater speed, confidence, and impact.
During this transition period, you may see references to both Fivetran and dbt Labs throughout our recruiting process as we integrate our teams, systems, and career sites.
About the Role
We’re looking for a Staff Software Engineer to join Cloud Signals, the team behind the systems that measure, bill, and talk to our customers across the dbt platform and, more and more, the combined Fivetran + dbt product.
Cloud Signals owns:
Billing and usage metering: turning product activity into accurate, auditable usage and billing data, and leading the integration of Fivetran and dbt billing into one consolidated system.
Vortex, our telemetry and event pipeline: high-volume event ingestion that feeds the warehouse, product analytics, and downstream systems.
The Notification System: the shared service that sends transactional and product notifications (email, in-app, Slack) for teams across the platform.
Usage and admin reporting: giving customers clear visibility into consumption as we move toward consumption-based pricing.
These systems are on the critical path for revenue and customer trust. As a Staff engineer you’ll set technical direction across them, take on the hardest cross-team problems, and help raise the bar for engineering across the area.
This is a full-time remote position.
Technologies You’ll Use
Python and TypeScript for backend services and APIs (Rust, Go, or Java experience also welcome)
Relational databases (PostgreSQL) and cloud data warehouses (Snowflake)
Event streaming and messaging systems (Kafka or similar) for high-throughput telemetry and usage pipelines
AWS (plus exposure to GCP or Azure), Docker, and Kubernetes
Terraform for infrastructure as code
Datadog for observability, alerting, and on-call
Third-party billing and payment platforms, plus internal and public REST APIs
AI coding assistants and agents (e.g., Claude Code) as part of everyday development
What You’ll Do
Own the technical direction for Cloud Signals’ systems: set architecture, write and socialize design docs, and turn ambiguous business goals (consolidated billing, consumption pricing, telemetry expansion) into clear, staged technical plans.
Lead the design and delivery of the Fivetran + dbt billing integration: data models, usage pipelines, reconciliation, and migration strategy, so that every customer is billed correctly and on time.
Evolve Vortex into a reliable, cost-efficient, scalable event platform: onboard new event types, cut operational dependencies and cost, and make sure data lands in the warehouse correctly and observably.
Grow the Notification System into a dependable shared service that other teams can adopt easily.
Work closely with Product, Finance, RevOps, Data, and partner engineering teams across both companies, often filling gaps in specs and prototyping to test ideas before you commit to a direction.
Raise operational excellence: define SLOs, improve alerting and runbooks, take part in on-call, and lead incident response and blameless postmortems for business-critical systems.
Mentor engineers at every level, give thoughtful code and design reviews, and set an example for engineering practices, including effective, responsible use of AI tools in the SDLC.
Work across teams, departments, and time zones as a technical partner to engineering leadership on roadmap, staffing, and build-vs-buy decisions.
Skills We’re Looking For
8+ years building and operating production software, with a track record of technical leadership on large, cross-team projects
Deep experience designing distributed systems and backend services, with a strong focus on correctness, idempotency, and data integrity
Hands-on experience with event-driven architectures and streaming or messaging systems (e.g., Kafka) at high volume
Strong knowledge of relational databases and data modeling, plus experience with cloud data warehouses such as Snowflake
Proven ability to design, build, and consume APIs and integrate with third-party systems
Production experience with at least one major cloud provider (AWS preferred), containers and orchestration (Docker, Kubernetes), and infrastructure as code (Terraform)
A strong operational mindset: observability (Datadog or similar), SLOs, on-call, incident management, and leading systems through migrations without downtime
The ability to spot design flaws in existing systems and lead incremental improvements while still shipping
Excellent written and verbal communication: you write clear design docs, align stakeholders with different priorities, and explain technical trade-offs to non-technical partners
Fluency with AI code assistants and coding agents for building features, fixing bugs, testing, and investigation, and with conversational AI (Claude, ChatGPT, internal chatbots) for researching, writing, and reviewing SDLC artifacts like TDDs, PRDs, postmortems, test plans, and proposals
Bonus Skills
Experience with billing, metering, or usage-based pricing systems (e.g., Metronome, Stripe, or in-house rating and invoicing)
Experience building telemetry or analytics pipelines (e.g., Snowplow, Iceberg, lakehouse architectures)
Experience building notification or messaging platforms (email, in-app, webhooks) at scale
Experience with data processing (ETL/ELT), dbt, or other modern data stack tools
Experience leading platform consolidation or system integration after a merger or acquisition