Description
As an engineer on the Data Team at Qualified, you'll operate as a technical leader on the layer everything else is built on. The team owns Qualified's data end to end: leads and accounts data models, ETL pipelines, Data 360, Salesforce sync, analytics and insights, data integrations, and Data APIs.
Responsibilities:
- Design and ship data systems end-to-end: models, pipelines, sync, and serving layers that the whole platform builds on
- Drive technical design for high-volume, multi-component systems (ETL, event streaming, analytics stores, APIs) with an emphasis on correctness, freshness, and operational excellence
- Own Salesforce data flows at enterprise scale
- Build the analytics and insights infrastructure that powers customer-facing reporting and internal decision-making
- Define data quality standards: SLOs, data contracts, observability, and the tooling to enforce them
- Own delivery from scope/design through launch, monitoring, and iterative improvement,anticipating risks, sequencing work, and aligning stakeholders
- Partner closely with product teams and engineering leadership to make data a first-class platform capability
- Raise team effectiveness through mentoring, technical guidance, code review, and improving standards, tooling, and processes
Requirements:
- Proven experience building and operating production data systems at scale: pipelines, data models, or high-volume backend services
- Strong depth in several of: PostgreSQL at scale, OLAP systems (ClickHouse or similar), CDC and event streaming, ETL orchestration, or data modeling for CRM-shaped domains
- Demonstrated technical leadership: you influence architecture and execution beyond your immediate workstream
- Strong track record delivering complex projects with multiple stakeholders, dependencies, or phases
- Comfortable operating in ambiguity and driving clarity: a newer team means the roadmap and conventions are still being written, and you find that energizing
- Pragmatic about reliability: you think in terms of data contracts, backfills, idempotency, and what happens when things fail
- Experience with modern stacks (Rails/Postgres/AWS is a plus; adaptability matters most)
Nice to Have:
- Experience supporting AI/ML or agentic products, where data freshness and grounding directly shape model behavior
- Experience with enterprise SaaS (especially B2B marketing or sales tech)
- Experience with real-time or event-driven systems
- Startup experience and rapid shipping
Benefits:
- Time off programs
- Medical, dental, vision
- Mental health support
- Paid parental leave
- Life and disability insurance
- 401(k)
- Employee stock purchasing program
The typical base salary range for this position is $172,500 - $260,100 annually. In select cities within the San Francisco and New York City metropolitan area, the base salary range for this role is $207,800 - $285,800 annually.