Principal Software Engineer- DataHub

HubSpot • Cambridge, MA

13h • Hybrid

About The Position

HubSpot’s Data Hub helps RevOps, marketing, sales, and customer teams turn fragmented data into actionable intelligence. We unify data across channels and tools, improve data quality, and activate it inside HubSpot so teams can run AI-powered demand generation, smarter campaigns and sales motions, agentic automations, trustworthy reporting, all without needing to be data experts. We’re a product engineering team at the intersection of data engineering, ML, applied AI, and go-to-market, and we care as much about reliability, cost, and scale as we do about time-to-value and usability for marketers and sales reps. We’re looking for a Principal Software Engineer to lead the next evolution of Data Hub as the backbone for data-driven demand generation.

Requirements

• Deep experience building large‑scale data systems with Apache Spark and modern table formats like Apache Iceberg, including efficient partitioning, clustering, and file layout for both heavy ingestion and low‑latency reads.
• Applies distributed systems principles and CAP theorem pragmatically to design fault‑tolerant, horizontally scalable services that balance availability, consistency, latency, and cost, where it matters.
• Can turn ambiguous business goals into clear data models, contracts, and SLAs across multiple storage and compute layers (e.g., Iceberg, warehouses, logs, CRM stores).

Nice To Haves

• If you enjoy working at the intersection of data engineering, ML, applied AI, and commercial outcomes, and you like building platforms that make complex data approachable for non-experts, we’d love to talk.

Responsibilities

• Own core pieces of our data lake and analytics stack (e.g., Iceberg, Spark, batch and streaming pipelines) that power demand gen, segmentation, and scoring at scale.
• Design and evolve data systems that balance cost, latency, data freshness, and reliability, making explicit tradeoffs using concepts like CAP theorem, efficient partitioning, and storage layout.
• Partner closely with PM, product analytics, and GTM leaders to shape commercially meaningful solutions: better lead scoring, funnel visibility, audience building, and campaign attribution for marketers and sales.
• Help make Data Hub an AI‑agent‑forward platform, where curated, evergreen datasets automatically feed AI agents and reporting surfaces rather than requiring manual stitching or ad-hoc pipelines.
• Influence technical direction across the Data Hub product line and shape the architecture for unified profiles, segmentation, and datasets that other teams can build on.
• Write code and build systems while leading end-to-end delivery of high-impact, multi-quarter initiatives, setting standards for reliability, observability, testing, and incident response.
• Define reusable patterns for ingestion, transformation, quality, sync, and observability, mentor senior engineers and tech leads.
• Actively use AI-assisted development tools to speed iteration, reduce toil (e.g., scaffolding, tests, refactors), and improve code quality, while defining best practices with the human‑in‑the‑loop approach.
• Break down big, ambiguous problems into incremental milestones that deliver value early and often, balancing long-term platform bets with clear business impact (ARR, adoption, usage, efficiency).
• Model strong habits around documentation, design reviews, testing, and observability, and help establish reliability and data quality standards so downstream AI agents and data activation use cases can trust the data they receive.

Benefits

• Annual Cash Compensation Range: $313,800—$502,080 USD
• Some roles are eligible to participate in HubSpot’s equity plan to receive restricted stock units (RSUs).
• Some roles may also be eligible for overtime pay.
• Explore the benefits and perks HubSpot offers to help employees grow better.

What This Job Offers

• Job Type: Full-time
• Career Level: Principal
• Education Level: No Education Listed
• Number of Employees: 1,001-5,000 employees