# Senior Data Engineer **Company**: ZoomInfo **Location**: London **Experience**: senior **Job type**: full-time **Category**: Engineering **Industry**: Technology **Apply**: https://job-boards.greenhouse.io/zoominfo/jobs/8779426002?utm_source=yubhub.co&utm_medium=jobs_feed&utm_campaign=apply **Canonical**: https://yubhub.co/jobs/job_035fe4b3-1b7 ## Description We are looking for a highly skilled Senior Data Engineer to become part of our core Enterprise Data Engineering team. You will be a senior member of the larger AI, Data and Innovation organization, responsible for designing and expanding enterprise-level data infrastructure that enables ZoomInfo's internal teams to interact with data comprehensively. Responsibilities: - Design, develop, and maintain high-performance, product-centric data pipelines using Airflow, DBT, and Python. - Architect and optimize the massive-scale data warehouse and lakehouse that serves as our single source of truth for all customer data, primarily using Snowflake. - Lead the integration of diverse structured and unstructured data sources into our data ecosystem, ensuring high-quality and reliable ingestion. - Define roadmap priorities that anticipate internal consumer needs and drive competitive advantage in data and AI capabilities. - Serve as a trusted advisor to leadership on strategy, AI-readiness, and data infrastructure investment decisions. - Collaborate with ML engineers, data scientists, and product managers to translate business needs into scalable data solutions that directly enhance customer value. - Define, monitor, and enforce data quality SLAs across all pipelines and products, ensuring data accuracy and lineage are a top priority. - Participate in a shared PagerDuty on-call rotation, responding to pipeline and platform incidents, performing root-cause analysis, and driving remediation and postmortems. - Triage production issues quickly and escalate appropriately, knowing when to loop in engineering leadership, Platform engineers, adjacent teams, or business stakeholders based on severity, blast radius, and customer impact. - Operate effectively amid ambiguity by making sound judgment calls and iterating with stakeholders rather than waiting for perfect clarity. - Mentor and coach junior engineers, promoting best practices in code quality, data architecture, incident response, and operational excellence. - Participate in architectural decisions and long-term strategy planning for our enterprise-wide data infrastructure, with a focus on cost, performance, reliability, and observability. - Contribute to and maintain runbooks, on-call documentation, and operational playbooks to reduce time-to-resolution for future incidents. Requirements: - Expert-level SQL for building performant, scalable queries and transformations on massive datasets. - Strong Python programming skills with a focus on distributed computing, data manipulation, and building robust APIs. - Production-level experience for large-scale batch and streaming data processing. - Hands-on experience with DBT (Data Build Tool) for advanced data modeling and transformations in a modern data stack. - Deep knowledge of Snowflake data warehouse design, optimization, and cost modeling. - Experience owning production systems, including on-call rotations, incident response, and postmortem processes. - Strong understanding of data architecture concepts, including data lakes, event-driven architectures, ETL/ELT, and data mesh. - Proficiency with cloud platforms (GCP and/or AWS) and infrastructure as code (e.g., Terraform). - Experience with monitoring/observability tooling for proactive detection of data quality and pipeline issues. - Familiarity with CI/CD practices applied to data workflows. Non-Technical Skills: - Excellent communication skills – ability to explain complex technical concepts to both engineering teams and non-technical stakeholders. - Strategic & Product-Oriented Thinking – can translate business objectives and customer needs into scalable, high-impact data solutions. - Leadership & Mentorship – experience guiding and uplifting engineering teams to achieve their full potential. - Stakeholder Management – able to collaborate effectively across departments and communicate clearly with the right people at the right time when issues arise. - Sound Judgment Under Ambiguity – comfortable making decisions with incomplete information, adjusting course as new data emerges, and knowing when to ask for help versus when to move forward independently. - Ownership & Accountability – takes responsibility for the full lifecycle of what you build, including production support, not just initial delivery. - Strong documentation habits and ability to evangelize best practices across the organization. ## Skills ### Required - SQL - Python - Airflow - DBT - Snowflake - Terraform - GCP - AWS - Datadog - Grafana --- Source: [Apply at job-boards.greenhouse.io](https://job-boards.greenhouse.io/zoominfo/jobs/8779426002?utm_source=yubhub.co&utm_medium=jobs_feed&utm_campaign=apply)