Senior Software Engineer

ZoomInfo•Waltham, MA

33d•Hybrid

About The Position

We're building the data processing platform that powers our core data products and go-to-market systems and handles billions of records of company and contact data. As a Senior Software Engineer on the Data Platform team, you'll design and build the foundational services and components that enable engineering teams across the organization to unify, validate, normalize, and enrich business data at scale. This is a backend engineering role where you'll work with familiar GTM data concepts-company firmographics, contact information, job titles, addresses-and build the reusable infrastructure that ensures data quality and consistency. Our Data Platform solves a real problem: teams across the organization need to perform common operations on business data, validating email addresses, normalizing phone numbers, standardizing company names, categorizing job titles, translating data between different languages, formats, and schemas. You'll build a centralized platform where these operations are implemented once as high-quality services, then made available through multiple access patterns: embeddable libraries for high-performance use cases, REST APIs for synchronous calls, pipeline components for data workflows, and streaming processors for real-time operations. Your work directly enables our GTM Studio platform, unified customer profile and entity resolution capabilities. The validation and normalization services you build ensure we can accurately match and merge records, giving downstream systems and applications clean, consistent data to work with.

Requirements

6+ years of software engineering experience with strong Java skills and a track record of building production services that other teams depend on
Strong proficiency with Java 11+ and Spring Boot 3.2+ (Spring WebMVC, Spring Data)
Experience deploying and operating services on Kubernetes, preferably GKE
Familiarity with Google Cloud Platform services (GCS, BigTable, or similar cloud storage and database solutions)
Experience building platform capabilities, frameworks, or reusable libraries that serve multiple engineering teams
Track record of building high-scale systems that handle millions of requests efficiently and reliably
Comfort working with GTM/CRM data domains (firmographic data, contact records, and common data quality challenges in B2B contexts)
Strong API design instincts and ability to build interfaces that are both powerful and easy to use
Experience with service-oriented architectures: building microservices, designing for backward compatibility, versioning strategies, service discovery
Track record of pragmatic engineering: you start simple, ship incrementally, and add complexity only when it's justified by real requirements
Ability to partner with other engineering teams by gathering requirements, understanding constraints, and building solutions that actually get adopted

Nice To Haves

Experience with data validation, normalization, or enrichment systems
Background in CRM platforms, customer data platforms, or marketing technology

Responsibilities

Build production-grade Java services that validate, normalize, and enrich business data (address standardization, phone number formatting, email validation, company name normalization, job title categorization) while handling tens of millions of daily requests
Design clean APIs and interfaces that let other engineers easily integrate these capabilities into their applications and data workflows
Integrate with third-party data providers (address validation services, phone intelligence APIs, business data vendors) and wrap them in consistent, reliable interfaces
Work on the platform itself: build the framework that lets teams discover services, understand versions, handle backward compatibility, and deploy new capabilities
Collaborate with product engineering teams to understand their data quality needs and translate those into reusable platform capabilities
Design caching strategies, batch optimization, and resource management to efficiently serve massive scale while controlling costs
Build observability, monitoring, and operational tooling so teams can use these services reliably in production

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