Salesforce

Senior Manager, Software Engineering - Telemetry Platform

California - San Francisco · Senior

Sponsorship not specified$173k-$260kDetected 5 days ago

JavaScriptiOSAndroidGitAWSTerraformDatadogPlatform EngineeringKafkaMachine LearningData EngineeringData ScienceAgentic AIA/B TestingProduct ManagementSalesforceCRMRecruitingCustomer Success

About the role

To get the best candidate experience, please consider applying for a maximum of 3 roles within 12 months to ensure you are not duplicating efforts.
And innovation isn't a buzzword - it's a way of life.
Ready to level-up your career at the company leading workforce transformation in the agentic era?

Responsibilities

You bring a strong background in schema-driven development, including schema registries, envelope design, event contract governance, and managing schema evolution across producers and consumers.
You're an experienced people manager with a track record of hiring, developing, and retaining engineers across varying seniority levels - building high-performing, inclusive teams.
You're familiar with privacy-by-design principles, including personally identifiable information (PII) handling, data residency, and compliance requirements in event data collection.

Requirements

A related technical degree required.
You have experience with distributed tracing and observability platforms such as OpenTelemetry, Sentry, Datadog, or Splunk.

Compensation

At Salesforce, we believe in equitable compensation practices that reflect the dynamic nature of labor markets across various regions.The typical base salary range for this position is $172,500 - $260,100 annually.

Benefits

Lead end-to-end delivery of core platform components, ensuring the pipeline reliably serves analytics, machine learning, and experimentation consumers with the data quality, latency, and availability each requires.
Partner with product, data engineering, analytics, and machine learning stakeholders to align on requirements, prioritize the roadmap, and drive telemetry adoption as the platform expands to new surfaces.
You've served diverse downstream consumers - including analytics/business intelligence, machine learning, and experimentation platforms - with a clear understanding of their data quality and latency requirements.
You can drive alignment across engineering, product, data science, and machine learning stakeholders, translating competing requirements into a shared technical roadmap.
You're familiar with AI and machine learning data pipeline requirements, including feature engineering, training data curation, and real-time inference, and how they shape telemetry structure and delivery.
It also applies to recruiting, hiring, job assignment, compensation, promotion, benefits, training, assessment of job performance, discipline, termination, and everything in between.
The same goes for compensation, benefits, promotions, transfers, reduction in workforce, recall, training, and education.
Certain roles may be eligible for incentive compensation, equity, and benefits.

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