# Senior Data Engineer

**Company**: ZoomInfo
**Location**: Dublin
**Work arrangement**: hybrid
**Experience**: senior
**Job type**: full-time
**Category**: Engineering
**Industry**: Technology

**Apply**: https://job-boards.greenhouse.io/zoominfo/jobs/8649162002?utm_source=yubhub.co&utm_medium=jobs_feed&utm_campaign=apply
**Canonical**: https://yubhub.co/jobs/job_1d78480c-93d

## 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.

The ideal candidate has a strong background in big data processing, pipeline orchestration, and data modeling, with a proven track record of delivering scalable and high-quality data solutions in fast-paced, data-centric product environments.

Given the dynamic nature of emerging technologies, this role requires an individual who excels at exploration and embraces continuous learning as core responsibilities.

**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 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.

- Strong understanding of data architecture concepts, including data lakes, event-driven architectures, ETL/ELT, and data mesh.

- Proficiency with cloud platforms and infrastructure as code.

- 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.

- Sound Judgment Under Ambiguity – comfortable making decisions with incomplete information.

- Ownership & Accountability – takes responsibility for the full lifecycle of what you build.

- Strong documentation habits and ability to evangelize best practices across the organization.

## Skills

### Required
- SQL
- Python
- Airflow
- DBT
- Snowflake
- data architecture
- data modeling
- big data processing
- pipeline orchestration
- cloud platforms
- infrastructure as code
- monitoring/observability tooling
- CI/CD practices

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Source: [Apply at job-boards.greenhouse.io](https://job-boards.greenhouse.io/zoominfo/jobs/8649162002?utm_source=yubhub.co&utm_medium=jobs_feed&utm_campaign=apply)