Staff Software Engineer (DIF)

Iterable•Boston, MA

About The Position

Iterable is the leading AI-powered customer engagement platform that helps leading brands like Redfin, SeatGeek, Priceline, Calm, and Box create dynamic, individualized experiences at scale. Our platform empowers organizations to activate customer data, design seamless cross-channel interactions, and optimize engagement—all with enterprise-grade security and compliance. Today, nearly 1,200 brands across 50+ countries rely on Iterable to drive growth, deepen customer relationships, and deliver joyful customer experiences. Our success is powered by extraordinary people who bring our core values—Trust, Growth Mindset, Balance, and Humility—to life. We foster a culture of innovation, collaboration, and inclusion, where ideas are valued and individuals are empowered to do their best work. That’s why we’ve been recognized as one of Inc’s Best Workplaces and Fastest Growing Companies, and were recognized on Forbes’ list of America’s Best Startup Employers in 2022. Notably, Iterable has also been listed on Wealthfront’s Career Launching Companies List and has held a top 10 ranking on the Top 25 Companies Where Women Want to Work. With a global presence—including offices in San Francisco, New York, Denver, London, and Lisbon, plus remote employees worldwide—we are committed to building a diverse and inclusive workplace. We welcome candidates from all backgrounds and encourage you to apply. Learn more about our story and mission on our Culture and About Us pages. Let’s shape the future of customer engagement together! How you will make an impact: The Data In Flight (DIF) team owns the core pipelines that ingest and route user and event data into Iterable, powering identity, segmentation, and real-time personalization. We are building a multi-tenant data platform that application teams can build on top of, with clear contracts, SLOs, and guardrails. Our product and our Elasticsearch clusters are multi-tenant, and we run Elasticsearch on Kubernetes using Elastic Cloud on Kubernetes (ECK). We’re looking for a Staff Software Engineer with a track record of operating Elasticsearch-backed data platforms in multi-tenant SaaS. You’ll be a hands-on IC who both designs distributed systems and acts as a platform “product owner” for app teams: understanding their needs, shaping the platform roadmap, and defining stable interfaces between product and data infrastructure.

Requirements

Hands-on Elasticsearch expertise in production:
Supporting customer-facing features or platforms backed by ES
Designing schemas and queries for high-cardinality, multi-tenant workloads
Operating large clusters (capacity planning, scaling, incident response)
Multi-tenant platform experience:
Building shared data services used by multiple product teams
Implementing rate limits, quotas, and noisy-neighbor protections
Thinking in terms of contracts and SLOs, not one-off integrations
Strong distributed systems background:
JVM-based services (Scala/Java) and event-driven or streaming architectures
Comfort with modern cloud infrastructure (AWS or similar), messaging, and caches
Staff-level impact and collaboration:
Leading cross-team projects from design through rollout
Translating technical decisions into clear business and product trade-offs
Clear written communication (RFCs, design docs, post-incident reviews)

Nice To Haves

Experience with Scala and the Play framework or similar JVM stacks.
Prior work on core user data platforms (identity, profile stores, event pipelines, or CDP-like systems).
Exposure to FinOps / infra cost optimization in data-heavy systems.
Experience in MarTech / AdTech or other high-volume, low-latency data domains.

Responsibilities

Own and evolve core Data In Flight services (ingestion, user and event APIs, identity, system events) with a focus on reliability, performance, and cost.
Lead the Elasticsearch strategy for our multi-tenant live user and event data: index and mapping design, shard strategy, and safeguards across shared clusters.
Design and enforce platform contracts (APIs, data models, SLAs, and usage limits) that let product teams move quickly while keeping the data platform safe and scalable.
Work across other data and application teams on initiatives such as Elasticsearch upgrades, guardrails, resharding, and event retention.
Provide senior technical leadership during incidents and reviews, turning operational learnings into durable platform improvements.
Mentor engineers on distributed systems, data modeling, and pragmatic use of Elasticsearch.