lever
Senior Manager, Data Platform Engineering
jobgether
Remote, USA
Full-time
Remote
$175,000–$195,000.
Discovered 2 weeks ago
Data platform engineeringPeople managementData ingestionETL/ELTDistributed data processingCloud data architecture
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Data platform engineeringPeople managementData ingestion
Role Overview
Senior engineering leadership role focused on scaling a modern data platform and the team behind it.
The role combines people leadership, technical judgment, and execution discipline to deliver reliable data capabilities.
The position partners with Product, Engineering, Architecture, Client Delivery, Operations, and business stakeholders.
The work supports scalable ingestion, transformation, lakehouse architecture, governance, and reusable platform capabilities.
Key Skills for This Role
Data platform engineeringPeople managementData ingestionETL/ELTDistributed data processingCloud data architecture
Full Job Posting
Role overview
Senior engineering leadership role focused on scaling a modern data platform and the team behind it.
The role combines people leadership, technical judgment, and execution discipline to deliver reliable data capabilities.
The position partners with Product, Engineering, Architecture, Client Delivery, Operations, and business stakeholders.
The work supports scalable ingestion, transformation, lakehouse architecture, governance, and reusable platform capabilities.
Accountabilities
- Lead, coach, and develop a high-performing Data Platform engineering team through expectations, career development, feedback, and performance management.
- Own complex data initiatives from planning through production with defined scope, milestones, dependencies, risks, and target dates.
- Maintain delivery accountability by addressing blockers, scope changes, capacity constraints, and technical risks.
- Evaluate architecture, estimates, technical readiness, root causes, and quality with Staff Engineers and other technical leaders.
- Drive production support, on-call readiness, incident management, data quality, observability, backup coverage, and corrective actions.
- Guide scalable data ingestion, ETL/ELT, distributed processing, lakehouse and cloud architecture, governance, and reusable platform capabilities.
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