Summary:

As a Principal Software Engineer on our Go To Market Store (GTM Store) and ZoomInfo Data Platform (ZDP) team, you'll play a pivotal role in developing ZoomInfo's next-generation unified data platform. You'll architect and implement infrastructure that powers our GraphQL-based federated query system for seamless data access across platforms including BigTable, BigQuery, and Solr+. This is a unique opportunity to influence the technical direction of ZoomInfo's core data infrastructure, addressing complex challenges such as data freshness, multi-tenant isolation, and real-time data processing at scale.

Responsibilities:

• Design and build scalable infrastructure for GTM Store and ZDP with sub-second query latency.
• Architect and implement metadata-driven GraphQL APIs for dynamic schema generation and query federation.
• Develop asynchronous secondary indexing systems for scaling capacity and reducing primary data store load.
• Design real-time analytics streaming data pipelines from BigTable to BigQuery.
• Develop data mutation and deletion frameworks supporting GDPR compliance and schema evolution.
• Implement CDC pipelines and calculated field processing for derived data views.
• Build observability and monitoring solutions for real-time issue diagnosis across distributed data systems.
• Create batch and streaming data processing workflows for complex relationships at scale.
• Collaborate with engineering leaders and product managers to define the technical roadmap.
• Mentor engineers and establish best practices for cloud-native data infrastructure development.
• Partner with cross-functional teams to address data platform requirements and challenges.
• Drive solutions for data freshness, query performance, and system reliability challenges.

Qualifications:

• Bachelor's degree in Computer Science, Software Engineering, or related field (or equivalent experience).
• 10+ years of software engineering experience building large-scale data platforms.
• Expertise with distributed NoSQL databases and data warehousing systems.
• Strong experience with Java 8+, Scala, Kotlin, GoLang for data systems development.
• Proven experience with GCP or AWS and cloud-native architectures.
• Experience with streaming/real-time data processing technologies.
• Strong system design skills for architecting multi-tenant, distributed systems.
• Hands-on experience with Google Cloud Platform services.
• Knowledge of CDC patterns, event sourcing, and streaming architectures.
• Experience solving data freshness and consistency challenges in distributed systems.
• Background in building observability and monitoring solutions for data platforms.
• Familiarity with metadata management and schema evolution.
• Experience with Kubernetes for deploying data services.
• SQL query optimization and performance tuning expertise.
• Experience building GraphQL APIs with federated or metadata-driven schema generation.
• Strong problem-solving skills and the ability to debug complex distributed systems issues.
• Excellent communication skills for explaining technical decisions to diverse audiences.
• Self-directed with the ability to drive initiatives independently while collaborating with teams.
• Passion for building reliable, observable, and maintainable systems.
• Experience promoting diverse, inclusive work environments.

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As a Senior Software Engineer on our Advertising, Company Intelligence, and Intent team, you’ll help design and implement the core systems that power our real-time marketing platform. From high-throughput ad infrastructure to large-scale identity resolution and intelligent systems enhanced by LLMs, push the boundaries of scale, intelligence, and speed—and deliver real-world business impact.

You’ll be joining a team with a broad range of ambitious, technically deep projects—from APIs that process tens of billions of events per day, to new buyer intent algorithms powered by LLMs, to a unified B2B identity graph. Depending on your strengths and interests, you’ll be matched to the initiatives where you can have the greatest impact.

This is a high-growth, high-ownership environment operating at the edge of what’s possible in modern software engineering, data infrastructure, and applied AI.

What You'll do:

• Design and build distributed systems that process, enrich, and respond to billions of behavioral events per day in real time
• Develop high-performance APIs and services that support advertising, identity, and intent features across the Marketing Platform
• Leverage machine learning and large language models (LLMs) to analyze behavioral data, classify content, extract signals, and enable intelligent decision-making
• Build intelligent agents using frameworks like LangGraph or MCP to reason over data and power user-facing insights
• Design and operate data pipelines using tools like Kafka, Kinesis, and ClickHouse to support both streaming and batch workloads
• Drive quality, performance, scalability, and observability across all systems you own
• Collaborate cross-functionally with product managers, data scientists, and engineers to deliver customer-facing features and internal tooling
• Contribute to technical leadership and mentorship of teammates. 

What you bring:

• 9+ years of backend, data, or infrastructure engineering experience, or equivalent impact and leadership.
• Distributed systems engineering (e.g., building low latency high and throughput APIs, scalable microservices, event processing pipelines)
• Big data infrastructure (e.g., streaming, warehousing, low-latency storage at scale)
• Applied AI/ML, including use of LLMs for extraction, classification, or reasoning tasks.
• Proficiency in one or more core languages: Java, Go, Python
• Solid grasp of SQL and large-scale data modeling
• Familiarity with databases and tools such as: ClickHouse, DynamoDB, Bigtable, Memcached, Kafka, Kinesis, Firehose, Airflow, Snowflake
• Comfortable using LLMs as part of your development workflow—whether via tools like Copilot, Cursor, ChatGPT, Claude, or others—to boost productivity, explore architecture ideas, and rapidly prototype.
• Skilled at designing and implementing LLM-powered systems such as RAG pipelines, agent frameworks (e.g., LangGraph), or intelligent workflows that reason across large datasets in real time.

Bonus Points:

• Experience in ad tech, real-time bidding (RTB), or programmatic systems
• Background in identity resolution, attribution, or behavioral analytics at scale
• Contributions to open source in ML, infrastructure, or data tooling
• Strong product instincts and a passion for building tools that drive meaningful outcomes

#LI-SK1

#LI-Remote

As a Principal Engineer on our Advertising, Company Intelligence, and Intent team, you’ll help design and implement the core systems that power our real-time marketing platform. From high-throughput ad infrastructure to large-scale identity resolution and intelligent systems enhanced by LLMs, push the boundaries of scale, intelligence, and speed—and deliver real-world business impact.

You’ll be joining a team with a broad range of ambitious, technically deep projects—from APIs that process tens of billions of events per day, to new buyer intent algorithms powered by LLMs, to a unified B2B identity graph. Depending on your strengths and interests, you’ll be matched to the initiatives where you can have the greatest impact.

This is a high-growth, high-ownership environment operating at the edge of what’s possible in modern software engineering, data infrastructure, and applied AI.

What You’ll Do

• Design and build distributed systems that process, enrich, and respond to billions of behavioral events per day in real time
• Develop high-performance APIs and services that support advertising, identity, and intent features across the Marketing Platform
• Leverage machine learning and large language models (LLMs) to analyze behavioral data, classify content, extract signals, and enable intelligent decision-making
• Build intelligent agents using frameworks like LangGraph or MCP to reason over data and power user-facing insights
• Design and operate data pipelines using tools like Kafka, Kinesis, and ClickHouse to support both streaming and batch workloads
• Drive quality, performance, scalability, and observability across all systems you own
• Collaborate cross-functionally with product managers, data scientists, and engineers to deliver customer-facing features and internal tooling
• Contribute to technical leadership and mentorship of teammates

What We’re Looking For

• 8+ years of backend, data, or infrastructure engineering experience, or equivalent impact and leadership.
  
  
• Strong experience in at least one of the following:
• Distributed systems engineering (e.g., building low latency high and throughput APIs, scalable microservices, event processing pipelines)
• Big data infrastructure (e.g., streaming, warehousing, low-latency storage at scale)
• Applied AI/ML, including use of LLMs for extraction, classification, or reasoning tasks
  
  
• Proficiency in one or more core languages: Java, Go, Python
• Solid grasp of SQL and large-scale data modeling
• Familiarity with databases and tools such as: ClickHouse, DynamoDB, Bigtable, Memcached, Kafka, Kinesis, Firehose, Airflow, Snowflake

AI-Native Development Mindset

• Comfortable using LLMs as part of your development workflow—whether via tools like Copilot, Cursor, ChatGPT, Claude, or others—to boost productivity, explore architecture ideas, and rapidly prototype.
  
  
• Skilled at designing and implementing LLM-powered systems such as RAG pipelines, agent frameworks (e.g., LangGraph), or intelligent workflows that reason across large datasets in real time.

Bonus Points

• Experience in ad tech, real-time bidding (RTB), or programmatic systems
• Background in identity resolution, attribution, or behavioral analytics at scale
• Contributions to open source in ML, infrastructure, or data tooling
• Strong product instincts and a passion for building tools that drive meaningful outcomes

#LI-SK1

#LI-Remote