Director of Engineering, Data Platform
Director of Engineering owning Pendo's Data Platform — real-time ingestion, batch pipelines, and analytics query engine processing 50B+ events/day at petabyte scale in Go on GCP (GKE, Pub/Sub, Firestore, Redis). Hybrid Raleigh, NC role: set architecture, own platform costs, partner with SRE, and coach managers.
- Compensation
- $235K–$280K / yr
- Location
- Raleigh, NC
- Work setup
- Hybrid
- Seniority
- Not specified
- Employment
- Not specified
- Experience
- Not specified
- Category
- Data engineering
- Posted
Skills
Must have
- Several years of engineering management experience, including managing managers or multiple teams; built high-performing teams in high-growth SaaS
- Experience building and operating large-scale, data-intensive distributed systems in production (ideally 50B+ events/day, petabyte scale)
- Strong experience across real-time data ingestion, batch processing, and analytics/query systems
- Cost and financial acumen at infrastructure scale: forecasting, optimization, attribution, overrun diagnosis; can build a credible cost model for technical and financial stakeholders
- Deep experience with diverse database technologies — relational (SQL), document (NoSQL), columnar, vector; Firestore or similar a strong plus
- Hands-on experience with multiple cloud platforms (GCP, AWS, Azure), including object storage and managed data services; deep GCP experience especially valuable
- Experience with message queuing/streaming (Pub/Sub, Kafka, SQS or similar), caching (Redis, Valkey, memcache), and Kubernetes workloads at scale
- Working knowledge of observability practices and tooling, ideally OpenTelemetry
- Comfort reading, reviewing, and contributing to Go code
- Credible communication with customers, executives, and engineers on complex topics; pragmatic judgment in ambiguity
Nice to have
- Experience with high-cardinality, high-volume event or telemetry data
- Background in multi-tenant SaaS 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
Full description
The team + the role
Pendo's Data Platform is the backbone of everything we do. Our systems process more than 50 billion events per day, peaking at over 1 million events per second, and manage dozens of petabytes of data across several production environments. The platform powers real-time data ingestion, batch processing, and analytics at scale — and the instrumentation standards that keep our entire codebase observable. It's built primarily in Go, runs on Google Kubernetes Engine, and relies on Cloud Pub/Sub, Firestore, Google Cloud Storage, Redis, and memcache. We expect the stack to evolve, and you'll help decide how.
We're looking for a Director of Engineering to lead the teams that own this infrastructure. This is a leadership role with real technical depth — you'll set strategy, build and grow high-performing engineering teams, and partner closely with Site Reliability Engineering. You'll stay close enough to the code to review designs, debug production issues, and contribute when it matters. You'll also own the economics of running the platform at this scale and be a trusted voice with customers on performance, data integrity, and reliability. If you want a role where architectural decisions have immediate business consequence and the technical bar is genuinely high, this is it.
This role is based in Raleigh, NC and follows Pendo's hybrid model: in-office 3 days per week.
What this looks like day-to-day
- Lead multiple engineering teams responsible for our real-time data ingestion pipeline, analytics batch job pipelines, and analytics query engine — setting 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; know when to adopt, build, or retire technologies and make those calls with conviction and clear rationale.
- Own instrumentation standards across the core codebase — structured logging, OpenTelemetry metrics and tracing — ensuring teams across the organization can adopt them with minimal friction and that the resulting telemetry is useful, consistent, and cost-conscious.
- Own the cost profile of the data platform at petabyte scale: forecast infrastructure spend for new product initiatives, improve cost attribution by customer, product, feature, and team, and diagnose and resolve cost overruns quickly.
- Partner with SRE on shared on-call responsibilities, incident response, postmortems, and reliability roadmaps; define and track SLOs for ingestion latency, query performance, and data correctness.
- Serve as a technical authority in customer conversations on platform performance, data integrity, and reliability — translating customer needs and escalations into clear engineering priorities.