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Pendo

SaaS platform for product analytics

Director of Engineering - Data Platform

Engineering LeadershipConfirmed live in the last 24 hours
Full-timeRaleigh, NC, USA

About the Job

Requirements

  • Several years of engineering management experience, including managing managers or multiple teams, and a track record of building high-performing teams in a high-growth software-as-a-service environment.
  • Demonstrated experience building and operating large-scale, data-intensive distributed systems in production, ideally at a scale comparable to 50 billion or more events per day and petabyte-level data management.
  • Strong experience across real-time data ingestion, batch processing, and analytics or query systems.
  • Demonstrated cost and financial acumen at infrastructure scale, including forecasting, optimization, attribution, and overrun diagnosis, and the ability to build a credible cost model and communicate its assumptions to technical and financial stakeholders.
  • Deep experience with relational (SQL), document (NoSQL), columnar, and vector database technologies.
  • Hands-on experience with multiple cloud platforms (Google Cloud Platform, Amazon Web Services, and Microsoft Azure), including object storage and managed data services; deep Google Cloud Platform experience is especially valuable.
  • Experience with message queuing and streaming systems such as Pub/Sub, Kafka, or SQS; caching technologies such as Redis, Valkey, or memcache; and containerized workloads on Kubernetes at scale.
  • Working knowledge of observability practices and tooling, ideally including OpenTelemetry, and comfort reading, reviewing, and contributing to Go code.
  • Ability to communicate credibly with customers, executives, and engineers on complex topics such as performance tradeoffs, consistency guarantees, and reliability commitments, and sound judgment in ambiguous situations.

Responsibilities

  • Lead multiple engineering teams responsible for real-time data ingestion, analytics batch job pipelines, and the analytics query engine; set technical direction and roadmap while balancing near-term delivery with long-term scalability, reliability, and cost efficiency.
  • Drive architectural decisions across storage, compute, and data modeling, deciding when to adopt, build, or retire technologies and explaining the rationale.
  • Own instrumentation standards across the core codebase, including structured logging and OpenTelemetry metrics and tracing; enable organization-wide adoption and ensure telemetry is useful, consistent, and cost-conscious.
  • Own the data platform cost profile at petabyte scale by forecasting infrastructure spend for new product initiatives, improving cost attribution by customer, product, feature, and team, and quickly diagnosing and resolving cost overruns.
  • Partner with Site Reliability Engineering on shared on-call responsibilities, incident response, postmortems, and reliability roadmaps; define and track service-level objectives for ingestion latency, query performance, and data correctness.
  • Serve as a technical authority in customer conversations about platform performance, data integrity, and reliability, translating customer needs and escalations into engineering priorities.
  • Hire, coach, and develop engineering managers and senior engineers; build a team culture grounded in high standards, clear communication, and continuous improvement.
  • Set architectural direction, make cost and reliability tradeoffs visible, and build teams capable of operating at a high level of ambition.
  • Evaluate emerging artificial intelligence tools, distinguish meaningful developments from hype, and guide adoption of AI-assisted and agentic coding practices across the organization while managing risk.
  • Review designs, debug production issues, and contribute to code when needed.
  • Partner with Site Reliability Engineering on platform reliability and serve as a trusted customer-facing technical voice.

Desired Qualifications

  • Experience with Firestore or a similar technology.
  • Experience with high-cardinality, high-volume event or telemetry data.
  • Background in multi-tenant software-as-a-service platforms.
  • Familiarity with FinOps practices and cloud billing data, including tagging, labeling, and usage-based cost attribution.
  • Contributions to open-source projects in the data or observability ecosystem.

About the Company

Pendo

SaaS platform for product analytics

Pendo provides a SaaS platform that helps software teams improve user experiences in their digital products. The platform integrates with a company’s existing software to collect user analytics, gather feedback, and deliver in-app messaging to guide users through features and updates. By turning user data into insights, Pendo helps product teams understand how people interact with their product and make data-driven decisions to improve engagement and adoption. What sets Pendo apart is its combination of analytics, feedback, and in-app guidance all in one connected platform, designed for a wide range of SaaS products from startups to enterprises. The company’s goal is to raise the quality of software experiences globally by helping teams create more valuable and easier-to-use products for their users.

Company size
501-1,000
Company stage
Growth Equity (Venture Capital)
Total funding
$468.3M
Headquarters
Raleigh, NC
Founded
2013

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