Principal Product Manager - Vertical Data at Zoominfo · LumiJobs
senior
$172k–$270k
H1B: yes
Zoominfo Principal Data Engineer to define and evolve architecture and engineering standards for enterprise data platform. Leads design of scalable, reliable, and secure data products across ingestion, storage, and consumption.
Responsibilities
Lead Data Architecture and System Design
Own the technical vision and architecture for scalable, resilient, and cost-effective data platforms and pipelines.
Design end-to-end data systems spanning batch and streaming ingestion, transformation, data modeling, storage, orchestration, serving layers, and consumption patterns.
Make and document high-quality architecture decisions, including tradeoffs involving performance, reliability, scalability, latency, security, maintainability, and cost.
Define reusable architectural patterns for common data engineering challenges, including CDC, event-driven data flows, schema evolution, slowly changing dimensions, data quality, and multi-tenant or domain-oriented data models.
Establish clear boundaries and interfaces between operational systems, data platforms, analytics layers, and downstream applications.
Lead technical design reviews for high-impact initiatives and provide clear, constructive direction on implementation approaches.
Identify architectural risks early and drive plans to mitigate technical debt, single points of failure, data inconsistency, and operational fragility.
Set Engineering Standards and Best Practices
Establish and continuously improve standards for data engineering development, testing, deployment, documentation, monitoring, incident response, and lifecycle management.
Define best practices for version-controlled data transformations, infrastructure as code, CI/CD, code review, automated testing, and environment promotion.
Build a culture of data reliability by implementing standards for data contracts, schema management, lineage, observability, freshness, completeness, accuracy, and reconciliation.
Qualification
Experience implementing data meshFamiliarity with data governanceExperience supporting financialExperience with ML data pipelinesLeadership CompetenciesSystems thinker
Preferred
Experience with cloud-native data platforms on AWS, Azure, or GCP.
Experience implementing data mesh, domain-oriented data product, or self-service platform patterns.
Familiarity with data governance, cataloging, lineage, privacy, and access-control tooling.
Experience supporting financial, revenue, operational, customer, or enterprise analytics domains.
Experience with ML data pipelines, feature stores, or AI/LLM data foundations.
Experience managing major data-platform migrations, modernization programs, or large-scale architectural transformations.
Leadership Competencies
Systems thinker: Connects individual technical decisions to broader platform, organizational, and business outcomes.
