Senior Manager, Software Engineering - Telemetry Platform

Salesforce•San Francisco, CA

1d•$172,500 - $285,800•Remote

About The Position

Join the Engineering Development and Delivery group within Salesforce's Digital Enterprise Technology organization, where you'll own the vision and execution of the Unified Telemetry platform — a foundational data infrastructure that powers analytics, machine learning, and experimentation across the company. This role is based in the United States and is built for a technical leader who thrives at the intersection of platform engineering, people development, and cross-functional influence in an era where AI-driven engineering is reshaping how we build and observe software.

Requirements

Hands-on experience designing and operating event streaming pipelines at scale, with deep familiarity with technologies like Kinesis, Kafka, or equivalent — including raw/bronze, cleansed/silver, and curated/gold data layer patterns.
Built or owned multi-platform client instrumentation, including Software Development Kits (SDKs) across mobile (iOS, Android) and web (JavaScript) surfaces.
Strong background in schema-driven development, including schema registries, envelope design, event contract governance, and managing schema evolution across producers and consumers.
Experienced people manager with a track record of hiring, developing, and retaining engineers across varying seniority levels — building high-performing, inclusive teams.
Strong Amazon Web Services (AWS) background, including experience with Fargate, Lambda, Kinesis, Identity and Access Management (IAM), and Terraform for infrastructure-as-code and secure, scalable service delivery.
Served diverse downstream consumers — including analytics/business intelligence, machine learning, and experimentation platforms — with a clear understanding of their data quality and latency requirements.
Ability to drive alignment across engineering, product, data science, and machine learning stakeholders, translating competing requirements into a shared technical roadmap.
A related technical degree required.

Nice To Haves

Experience with agentic Software Development Life Cycle (SDLC) tooling such as GitHub Copilot, Cursor, or similar AI-assisted development workflows — and a track record of driving adoption across engineering teams.
Familiarity 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.
Experience with data quality frameworks including automated validation, anomaly detection, and service-level agreement (SLA) monitoring for streaming pipelines.
Experience with distributed tracing and observability platforms such as OpenTelemetry, Sentry, Datadog, or Splunk.
Driven developer experience improvements — making it easier for product teams to instrument and adopt telemetry SDKs.
Familiarity with privacy-by-design principles, including personally identifiable information (PII) handling, data residency, and compliance requirements in event data collection.
Background in experimentation platforms and understanding the role telemetry plays in A/B testing and feature flagging infrastructure.

Responsibilities

Own the technical roadmap for the Unified Telemetry platform, driving architecture decisions across unified client SDKs, schema registry, and the ingestion layer — setting the engineering standard for telemetry across the organization.
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.
Build, grow, and mentor a high-performing team of engineers — establishing operational norms, fostering a culture of ownership and continuous improvement, and running career development conversations that help each person reach their potential.
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.
Champion the migration away from fragmented, bespoke telemetry approaches, representing the platform in org-wide planning and technical forums and advocating for telemetry as a shared observability backbone.