Engineering Manager

Salesforce•California - Remote, CA

16d

About The Position

We are looking for an experienced Engineering Manager to build and lead our new Data team. This is a high-impact leadership role focused on owning Qualified's data layer end to end: the models, pipelines, sync, and analytics that every product area and every AI agent we ship depends on. The team is already about half staffed, with a clear set of systems to own; you'll hire the rest, set the roadmap, and raise the bar for data quality and reliability across the platform. You'll partner closely with senior technical leaders and help drive execution across enterprise data integrations, analytics infrastructure, and the Salesforce ecosystem. We're looking for someone capable of building a team from the ground up with operational excellence and technical fluency, while bringing people leadership to the table.

Requirements

Experience managing engineering teams building data platforms, pipelines, or high-scale backend systems, ideally in high-growth environments.
Strong hiring instincts: you can source, close, and ramp strong engineers.
Strong technical depth in several of: PostgreSQL at scale, ClickHouse or similar OLAP systems, CDC and event streaming, ETL orchestration, or data modeling for CRM-shaped domains.
Comfort operating in ambiguity: this team has a charter and a backlog of expectations, but no established roadmap or conventions yet.
A "driver" mindset: proactive, outcomes-oriented, and unafraid to roll up your sleeves when needed.
Strong communication and collaboration skills, especially with stakeholders who don't work on data all day.

Responsibilities

Build and Grow the Team: Lead hiring against a higher bar, own the interview loop, and shape the team's identity, rituals, and standards.
Own the Data Charter & Roadmap: Take ownership of leads and accounts data models, ETL pipelines, Data 360, Salesforce sync, analytics and insights, data integrations, and Data APIs. Turn a set of inherited systems into a coherent platform strategy, and sequence the investments with engineering and product leadership.
Drive Data Architecture & Engineering Excellence: Guide end-to-end technical decisions across data modeling, ingestion, sync, and serving. Ensure the data layer is correct, fresh, observable, and easy for other teams to build on as the platform grows.
Champion Data Quality & Reliability: Define what good looks like: SLOs, data contracts, and the operational discipline to back them. Every product team and every AI agent depends on this layer being trustworthy.
Collaborate Cross-Functionally: Partner with leadership, product teams, and Salesforce counterparts to align on priorities, ensuring data is integrated into strategic decision-making and delivering results that move the business forward.