Principal Data Engineer

Zoominfo; United States; Remote; USD 172,000 - 270,000; Full time

Benefits offered by this job

Wellbeing programs

Job summary

ZoomInfo is seeking a senior data platform engineering leader to set the technical direction for the enterprise data platform. This hands-on role spans the full data lifecycle, shaping systems that deliver reliable, secure, and timely data to analytics, applications, and business teams.

You will design scalable data platforms and pipelines across batch and streaming processes, document architecture choices, and establish reusable patterns for data integration, governance, and data quality.

Qualifications

• 10+ years in software, data, platform engineering.
• Strong end-to-end design experience across data lifecycles.
• Proficiency in SQL and a general-purpose language (Python/Java/Scala).

Responsibilities

• Design and guide scalable data platforms across batch and streaming ingestion, transformation, storage, orchestration, serving, and consumption.
• Document architecture choices and tradeoffs around performance, reliability, and cost.
• Establish reusable patterns for data integration, event flows, schema changes, and governance.
• Set practices for testing, deployment, monitoring, and incident response.
• Lead technical reviews, mentor engineers, and develop templates and playbooks.

Skills

System design

Engineering leadership

SQL

Python/Java/Scala

Data architectures

Tools

Spark

Kafka

Flink

Snowflake

Databricks

BigQuery

Redshift

Job description

Role overview

Set the technical direction and engineering standards for an enterprise data platform. This hands-on technical leadership role spans the full data lifecycle, shaping systems that make reliable, secure, and timely data useful to analytics, applications, and business teams.

Responsibilities

• Design and guide scalable data platforms and pipelines across batch and streaming ingestion, transformation, storage, orchestration, serving, and consumption.
• Document architecture choices and tradeoffs involving performance, reliability, scale, latency, security, maintainability, and cost.
• Establish reusable patterns for data integration, event flows, schema changes, data quality, and domain-oriented models.
• Set practices for testing, deployment, monitoring, incident response, infrastructure, access controls, governance, and data lifecycle management.
• Lead technical reviews and cross-team decisions, assess platform options, and address architectural risks and technical debt.
• Mentor engineers, run design and knowledge-sharing sessions, and develop templates and playbooks that help teams deliver consistent data products.

Requirements

• 10 or more years in software, data, platform engineering, or a related technical field, including 5 or more years designing and operating large-scale data systems or products.
• Strong end-to-end system design experience, from requirements and tradeoffs through production delivery.
• Knowledge of modern data architecture, including warehouse or lakehouse platforms, batch and streaming, modeling, orchestration, metadata, and governance.
• Proficiency in SQL and a general-purpose language such as Python, Java, or Scala.
• Experience with distributed data technologies and platforms such as Spark, Kafka, Flink, Snowflake, Databricks, BigQuery, or Redshift.
• Ability to establish engineering standards and influence technical decisions across teams; strong written and verbal communication.

Nice to have

• Familiarity with tools and platforms such as Airflow, dbt, cloud data warehouses, data integration frameworks, and monitoring or data-quality systems.

Benefits and work setup

• The listing gives a US base salary range of $171,500-$269,500. Additional compensation may apply; the offer depends on location, qualifications, skills, and experience.
• Benefits and wellbeing programs are mentioned, but specific plan details are not provided.