Engineering Manager: Data Platform & AI Systems Lead

Leadout Capital; California; On-site; USD 180,000 - 250,000; Full time

Job summary

Leadout Capital is seeking an Engineering Manager to build and lead our new Data team. You will own data models, ETL pipelines, Data 360, Salesforce sync, analytics, and data APIs. The role requires hiring and shaping the team, setting direction, and raising data quality across the platform.

You will partner with senior tech leaders to drive enterprise data integrations, analytics infrastructure, and Salesforce ecosystem efforts. Strong leadership and data fluency are essential.

Qualifications

• Experience leading engineering teams building data platforms, pipelines, or high-scale backend systems.
• Strong hiring instincts: ability to source, close, and ramp engineers.
• Strong technical depth in data systems (PostgreSQL, OLAP like ClickHouse, CDC, ETL, or CRM data modeling).
• Comfort with ambiguity and building a roadmap from scratch.
• Driver mindset: proactive, outcomes-focused, hands-on when needed.
• Excellent communication and collaboration with stakeholders outside data.

Responsibilities

• Lead hiring against a high bar and own interview loop.
• Own the Data charter and roadmap, data models, ETL pipelines, and Data APIs.
• Guide end-to-end data architecture and engineering excellence across modeling, ingestion, sync, and serving.
• Define data quality disciplines: SLOs, data contracts, and operational discipline.
• Collaborate across leadership, product, and Salesforce counterparts to align priorities.

Skills

Engineering management

Data platform

PostgreSQL

ClickHouse

CDC

ETL

Data modeling

Hiring

Communication

Job description

Leadout Capital is seeking an Engineering Manager to build and lead our new Data team. You will own data models, ETL pipelines, Data 360, Salesforce sync, analytics, and data APIs. The role requires hiring and shaping the team, setting direction, and raising data quality across the platform.

You will partner with senior tech leaders to drive enterprise data integrations, analytics infrastructure, and Salesforce ecosystem efforts. Strong leadership and data fluency are essential.