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Senior Data Engineer

RemoteIreland only
Published
Role
Data Engineering
Experience
Lead
Company size
Enterprise
Salary not disclosed
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No BS summary

Senior Data Engineer with 8+ years in data engineering, big data pipelines, SQL, Python, DBT, Snowflake, cloud, and production on-call ownership. Must be able to design enterprise-scale data infrastructure for AI/data products and mentor junior engineers. Role is tied to Dublin and marked remote.

Core skills

SQLPythonSnowflake

Required skills

DBTGCP/AWSTerraform

Optional skills

AirflowPagerDutyOpsgenieKafkaDatadogMonte CarloGrafanaCI/CD

What you'll do

  • 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 the 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 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 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.

What they require

  • 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.
  • Experience with monitoring/observability tooling for proactive detection of data quality and pipeline issues.
  • Familiarity with CI/CD practices applied to data workflows.
  • Excellent communication skills – ability to explain complex technical concepts to both engineering teams and non-technical stakeholders, especially during high-pressure incidents.
  • 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.
  • Bachelor's or Master's degree in Computer Science, Engineering, or a related field.
  • 8+ years of progressive experience in data engineering, with a track record of leadership and impact.
  • Demonstrated experience in implementing or scaling data infrastructure for a data-centric product company.
  • Experience participating in an on-call rotation supporting production data systems.

Benefits

  • Tools that amplify your impact.
  • A culture that backs your ambition.

ZoomInfo (NASDAQ: GTM) is the Go-To-Market Intelligence Platform that empowers businesses to grow faster with AI-ready insights, trusted data, and advanced automation. Its solutions provide more than 35,000 companies worldwide with a complete view of their customers, making every seller their best seller.

🇺🇸 United StatesSales IntelligenceEnterprisezoominfo.com

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