Senior Data Engineer

We are looking for a highly skilled Senior Data Engineer to become part of our core Enterprise Data Engineering team.

You will be a senior member of the larger AI, Data and Innovation organization, responsible for designing and expanding enterprise-level data infrastructure that enables ZoomInfo's internal teams to interact with data comprehensively.

The ideal candidate has a strong background in big data processing, pipeline orchestration, and data modeling, with a proven track record of delivering scalable and high-quality data solutions in fast-paced, data-centric product environments.

Given the dynamic nature of emerging technologies, this role requires an individual who excels at exploration and embraces continuous learning as core responsibilities.

Responsibilities

• Design, develop, and maintain high-performance, product-centric data pipelines using Airflow, DBT, and Python.
• Architect and optimize the massive-scale data warehouse and lakehouse that serves as our single source of truth for all customer data, primarily using Snowflake.
• Lead the integration of diverse structured and unstructured data sources into our data ecosystem, ensuring high-quality and reliable ingestion.
• Define roadmap priorities that anticipate internal consumer needs and drive competitive advantage in data and AI capabilities.
• Serve as a trusted advisor to leadership on strategy, AI-readiness, and data infrastructure investment decisions.
• Collaborate with ML engineers, data scientists, and product managers to translate business needs into scalable data solutions that directly enhance customer value.
• Define, monitor, and enforce data quality SLAs across all pipelines and products, ensuring data accuracy and lineage are a top priority.
• Participate in a shared PagerDuty on-call rotation, responding to pipeline and platform incidents, performing root-cause analysis, and driving remediation and postmortems.
• Triage production issues quickly and escalate appropriately, knowing when to loop in engineering leadership, Platform engineers, adjacent teams, or business stakeholders based on severity, blast radius, and customer impact.
• Operate effectively amid ambiguity by making sound judgment calls and iterating with stakeholders rather than waiting for perfect clarity.
• Mentor and coach junior engineers, promoting best practices in code quality, data architecture, incident response, and operational excellence.
• Participate in architectural decisions and long-term strategy planning for our enterprise-wide data infrastructure, with a focus on cost, performance, reliability, and observability.
• Contribute to and maintain runbooks, on-call documentation, and operational playbooks to reduce time-to-resolution for future incidents.

Requirements

• Expert-level SQL for building performant, scalable queries and transformations on massive datasets.
• Strong Python programming skills with a focus on distributed computing, data manipulation, and building robust APIs.
• Production-level experience for large-scale batch and streaming data processing.
• Hands-on experience with DBT for advanced data modeling and transformations in a modern data stack.
• Deep knowledge of Snowflake data warehouse design, optimization, and cost modeling.
• Experience owning production systems, including on-call rotations.
• Strong understanding of data architecture concepts, including data lakes, event-driven architectures, ETL/ELT, and data mesh.
• Proficiency with cloud platforms and infrastructure as code.
• Experience with monitoring/observability tooling for proactive detection of data quality and pipeline issues.
• Familiarity with CI/CD practices applied to data workflows.

Non-Technical Skills

• Excellent communication skills – ability to explain complex technical concepts to both engineering teams and non-technical stakeholders.
• Strategic & Product-Oriented Thinking – can translate business objectives and customer needs into scalable, high-impact data solutions.
• Leadership & Mentorship – experience guiding and uplifting engineering teams to achieve their full potential.
• Stakeholder Management – able to collaborate effectively across departments.
• Sound Judgment Under Ambiguity – comfortable making decisions with incomplete information.
• Ownership & Accountability – takes responsibility for the full lifecycle of what you build.
• Strong documentation habits and ability to evangelize best practices across the organization.