Senior Manager, Software Engineering - Telemetry Platform

Role Overview

This position is part of the Engineering Development and Delivery group within the Digital Enterprise Technology organization. The engineer will own the vision and execution of the Unified Telemetry platform, a foundational data infrastructure that powers analytics, machine learning, and experimentation across the company.

• Own the technical roadmap for the Unified Telemetry platform, driving architecture decisions across unified client SDKs, schema registry, and the ingestion layer.
• Lead end‑to‑end delivery of core platform components, ensuring the pipeline reliably serves analytics, machine learning, and experimentation consumers with required data quality, latency, and availability.
• Build, grow, and mentor a high‑performing engineering team, establishing operational norms, fostering a culture of ownership and continuous improvement, and running career development conversations.
• 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.

• Hands‑on experience designing and operating event streaming pipelines at scale, with deep familiarity with technologies such as 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.
• Experience as a people manager with a track record of hiring, developing, and retaining engineers across varying seniority levels, building high‑performing, inclusive teams.
• Strong AWS background, including experience with Fargate, Lambda, Kinesis, IAM, and Terraform for infrastructure‑as‑code and secure, scalable service delivery.
• Experience serving diverse downstream consumers — analytics, 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.
• Related technical degree required.

• Experience with agentic SDLC tooling (e.g., Git Hub Copilot, Cursor) and a track record of driving adoption across engineering teams.
• Familiarity with AI and machine learning data pipeline requirements, 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 SLA monitoring for streaming pipelines.
• Experience with distributed tracing and observability platforms such as Open Telemetry, Sentry, Datadog, or Splunk.
• Experience driving developer experience improvements, making it easier for product teams to instrument and adopt telemetry SDKs.
• Familiarity with privacy‑by‑design principles, including PII handling, data residency, and compliance requirements in event data collection.
• Background in experimentation platforms and understanding of the role telemetry plays in A/B testing and feature‑flagging infrastructure.

• Base salary range: $172,500 – $260,100 annually (U.S. only). In select cities within the San Francisco and New York City metropolitan area the range is $207,800 – $285,800 annually.
• Benefits include time‑off programs, medical, dental, vision, mental health support, paid parental leave, life and disability insurance, 401(k), and an employee stock purchasing program.
• Additional compensation may include incentive compensation, equity, and other benefits.

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