Senior Analytics Engineer

Join ZoomInfo as a Senior Analytics Engineer and play a crucial role in advancing the maturity of our data organization. You will design, build, and own the core infrastructure and data models that drive data-driven decision-making across the organization. Collaborate with cross-functional teams, establish best practices for analytics engineering, and communicate technical concepts clearly to both technical and non-technical audiences. Enjoy competitive compensation, equity awards, flexible paid time off, and a hybrid working model.

- Design, develop, and maintain scalable analytics data models that support reporting, business intelligence, product analytics, and operational decision-making. - Build and manage trusted data pipelines and transformation workflows using modern analytics engineering practices. - Collaborate with data engineers and platform teams to optimize data architecture, warehouse performance, and transformation workflows.

- Experience working with modern cloud data warehouses such as Snowflake, Databricks, BigQuery, or Redshift - Strong SQL skills, including experience developing complex queries and dimensional data models - Strong communication, problem-solving, and organizational skills - 4+ years of experience in analytics engineering, data engineering, business intelligence engineering, or a related field - Experience building and maintaining analytics transformations using tools such as dbt or comparable frameworks - Proficiency in Python or another programming language used for data processing and automation - A thoughtful approach to data governance, security, privacy, and responsible use of data - Familiarity with data cataloging and lineage tools - Strong understanding of data modeling concepts, including dimensional modeling, fact and dimension tables, slowly changing dimensions, and semantic layers - Demonstrated ability to partner with cross-functional stakeholders and translate ambiguous business questions into scalable data solutions - Experience implementing data quality testing, monitoring, documentation, and observability practices