Software Engineering LMTS - Data (Remote)
Overview:
As an Engineer on the Data Team, you will own the data layer that powers Qualified's platform and AI agents. You'll shape end-to-end data systems, data models, and pipelines, ensuring freshness, scale, and reliability. You'll partner with product and engineering leadership to treat data as a core platform capability and influence enterprise-wide decisions. This role offers greenfield work on a data platform that directly enables AI-assisted products at scale. Join a high-ownership, startup-like team backed by Salesforce resources. Compensation / Benefitsmedical, dental, visionpaid parental leave 401(k)employee stock purchasing programmental health supportlife and disability insurance
Responsibilities:
- Design and ship data systems end-to-end (models, pipelines, sync, serving layers) used by the platform
- Lead high-volume, multi-component system designs (ETL, event streaming, analytics stores, APIs) with a focus on correctness and reliability
- Own Salesforce data flows at enterprise scale
- Build analytics and insights infrastructure for customer-facing reporting and internal decisions
- Define data quality standards (SLOs, data contracts, observability) and tooling
- Deliver from scoping to launch and monitor iterative improvements, managing risks and stakeholder alignment
- Collaborate with product teams and engineering leadership to make data a first-class platform capability
- Mentor team members, raise standards, improve tooling, and enhance processes
Key requirements:
- Proven experience building and operating production data systems at scale
- Strong depth in one or more: PostgreSQL at scale, OLAP (ClickHouse or similar), CDC/event streaming, ETL orchestration, or data modeling for CRM domains
- Demonstrated technical leadership and influence beyond own workstream
- Track record delivering complex, multi-stakeholder projects
- Comfort with ambiguity and ability to create clarity in a newer team
- Practical focus on reliability, data contracts, backfills, idempotency, and failure handling
- Experience with modern stacks (Rails/Postgres/AWS preferred; adaptability valued)cross-functional collaborationmentoring and technical guidanceproblem solving under ambiguity
- PostgreSQL at scaleOLAP systems (ClickHouse or similar)CDC and event streaming