Senior Data Engineer

About ZoomInfo

ZoomInfo is a dynamic Go-To-Market Intelligence Platform listed on NASDAQ (GTM) that accelerates business growth by delivering AI-enhanced insights, reliable data, and sophisticated automation. Serving over 35,000 companies globally, ZoomInfo equips businesses to optimize customer engagement and sales effectiveness.

Role Overview

We seek a Senior Data Engineer to join our central Enterprise Data Engineering group within the AI, Data, and Innovation division. This senior position involves architecting and scaling enterprise data infrastructure to comprehensively support internal team data interactions at ZoomInfo.

Key Responsibilities

• Create, develop, and sustain efficient, product-focused data pipelines utilizing Airflow, DBT, and Python.
• Design and enhance a large-scale data warehouse and lakehouse environment primarily on Snowflake that acts as a unified source for all customer data.
• Integrate a vast array of structured and unstructured data inputs, including web data and third-party APIs, ensuring reliable, accurate ingestion.
• Strategize the development roadmap reflecting internal users' needs to maintain competitive advantage through data and AI innovation.
• Act as a strategic consultant to leadership on data infrastructure investments and AI readiness.
• Work closely with machine learning engineers, data scientists, and product teams to transform business requirements into scalable data solutions that add direct value to customers.
• Enforce and track data quality standards, ensuring accuracy and lineage integrity across pipelines.
• Participate in an on-call rotation handling pipeline and platform incidents, conducting root cause analyses and leading remediation efforts.
• Efficiently triage production issues, escalating appropriately based on impact, scope, and severity while coordinating with various teams.
• Navigate ambiguity with sound judgment, iterating with stakeholders without waiting for perfect clarity.
• Mentor junior engineers to uphold best practices in code quality, architecture, and incident management.
• Contribute to architectural decisions and long-term planning for data infrastructure focusing on cost-efficiency, performance, reliability, and monitoring.
• Maintain operational documentation, including runbooks and incident playbooks, to improve resolution times.

Candidate Profile

• Expert proficiency in SQL for building scalable, high-performance queries and data transformations on large datasets.
• Advanced Python programming skills with emphasis on distributed computing, data manipulation, and robust API development.
• Demonstrated experience managing batch and streaming data processing at production scale.
• Strong hands-on expertise with DBT for sophisticated data modeling and transformations within modern data architectures.
• Deep understanding of Snowflake warehouse design and cost optimization strategies.
• Proven production system ownership experience including on-call rotations, incident investigation, and postmortem processes.
• Comprehensive knowledge of data architecture paradigms including data lakes, event-driven systems like Kafka, ETL/ELT workflows, and data mesh concepts.
• Familiarity with cloud platforms such as Google Cloud Platform and/or AWS, along with infrastructure as code tools like Terraform.
• Experience using monitoring and observability platforms (e.g., Datadog, Monte Carlo, Grafana) for proactive data quality detection.
• Application of continuous integration and continuous deployment principles to data workflows, including automated testing and version control.

Essential Non-Technical Skills

• Exceptional ability to communicate complex technical ideas clearly to both technical peers and non-technical stakeholders, particularly during high-pressure situations.
• Strategic mindset capable of aligning data solutions with overarching business goals and customer expectations.
• Leadership qualities including mentoring and uplifting engineering teams to meet high standards and growth.
• Strong cross-functional collaboration skills across Product, Engineering, Sales, and Compliance functions with timely communication during incidents.
• Capability to make informed decisions in uncertain scenarios and adjust strategies as new information arises.
• A strong sense of ownership over projects including delivery and ongoing production support.
• Meticulous documentation practices and advocacy for organizational best practices.

Educational and Experience Requirements

• Possession of a Bachelor’s or Master’s degree in Computer Science, Engineering, or related disciplines.
• At least 8 years of growing experience in data engineering demonstrating leadership and tangible business impact.
• Experience designing or scaling data infrastructure tailored for data-centric product companies.
• Active participation in on-call rotations supporting production data environments.

Additional Information

Applicants’ privacy is prioritized throughout the hiring process. As part of recruitment, a software-based assessment may be used. ZoomInfo prides itself on equal opportunity employment and inclusivity regardless of legally protected characteristics. Legal disclaimers are provided regarding lie detector test prohibitions, particularly for Massachusetts applicants.