Senior Data Analyst

About the role :

ZoomInfo is seeking a Senior Data Analyst to join the Data Operations and Analysis team, supporting the broader Data organization and partnering closely with Product, Engineering, and Research. This role focuses on driving strategic improvements in data infrastructure, pipeline design, data quality, and analytics at scale. The ideal candidate will design scalable data solutions, automate complex workflows, and transform structured and unstructured data into actionable insights. In addition to delivering advanced technical and analytical solutions, the Senior Data Analyst will influence data strategy, define KPIs and measurement frameworks, mentor junior analysts, and play a key role in enhancing the quality and long-term success of ZoomInfo's data assets.

What you’ll do

• Develop a deep understanding of ZoomInfo's data assets, infrastructure, and data operations to identify opportunities for improving data quality, accuracy, coverage, and scalability.
• Design, build, and optimize scalable cloud-native data pipelines and automation solutions using SQL(Snowflake), BigQuery, Python, Databricks, PySpark, Spark, and ETL/ELT frameworks.
• Leverage AI/GenAI/LLMs (including Claude Code), AI integrations, MCPs, APIs, and web scraping technologies to automate data acquisition, enrichment, validation, and processing.
• Analyze large structured and unstructured datasets, design experiments, validate hypotheses, and deliver actionable insights through dashboards, KPIs, and reporting frameworks.
• Partner closely with Data Engineering, Product Management, and Research teams to drive strategic data initiatives from discovery through implementation.
• Lead end-to-end delivery of large-scale, cross-functional data projects while maintaining rigorous data quality standards across pipelines and deliverables.
• Translate complex technical analyses into clear, business-focused recommendations for both technical and non-technical stakeholders.
• Mentor and coach junior analysts, contribute to hiring and foster a culture of continuous learning, technical excellence, and collaboration.
• Demonstrate strong problem-solving, curiosity, and self-driven ownership by proactively exploring data, proposing innovative solutions, and driving measurable business outcomes.

What You'll Bring:

• 7+ years of experience in Data Analytics / Data Operations / Data Engineering or Science, or a related field, with experience working in product- or project-driven environments.
• Strong expertise with hands-on experience in SQL, Snowflake, BigQuery, Python, PySpark, Apache Spark, Databricks, AWS, GCP, ETL/ELT pipeline development, REST APIs, and Excel, with proven experience handling large-scale structured and unstructured datasets.
• Hands-on experience with AI/GenAI/LLMs, including machine learning, NLP, prompt engineering, Claude Code, AI integration into Python applications, MCP (Model Context Protocol) integrations, and building AI-driven automation solutions.
• Strong experience in web scraping and data acquisition using tools sluch as Scrapy, Selenium, BeautifulSoup, and Playwright, along with a solid understanding of data quality, validation, enrichment, and governance.
• Excellent analytical, problem-solving, and communication skills, with the ability to simplify complex analyses into actionable insights and effectively present findings to both technical and non-technical stakeholders.
• Proven ability to manage multiple concurrent projects, lead cross-functional initiatives, mentor junior analysts, and work independently with a high degree of ownership and accountability.
• Experience building dashboards and reporting frameworks using visualization tools such as Tableau, Looker, or Power BI.
• Detail-oriented, highly organized, and intellectually curious, with a passion for continuous learning, improving data quality at scale, and driving innovative, data-driven solutions.
• Demonstrated experience leading and mentoring teams, providing technical guidance, coaching junior analysts, driving knowledge sharing, and successfully delivering cross-functional data initiatives.