Senior Data Engineer
HybridDublin, Leinster, Ireland
Job Summary
Design, develop, and maintain high-performance data pipelines using Airflow, DBT, and Python to integrate diverse structured and unstructured sources into our enterprise data ecosystem. Architect and optimize the massive-scale Snowflake data warehouse and lakehouse serving as the single source of truth for customer data. Lead integration of web data and third-party APIs while defining roadmap priorities to drive competitive advantage in data and AI capabilities. Share production ownership through a shared PagerDuty on-call rotation, triaging incidents, performing root-cause analysis, and driving remediation. Mentor junior engineers and collaborate with ML teams to translate business needs into scalable solutions. Serve as a trusted advisor on strategy, AI-readiness, and infrastructure investment decisions.
Required Qualifications
- 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 (e.g., PagerDuty, Opsgenie), incident response, and postmortem processes
- Strong understanding of data architecture concepts, including data lakes, event-driven architectures (e.g., Kafka), 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 (e.g., Datadog, Monte Carlo, Grafana) for proactive detection of data quality and pipeline issues
- Familiarity with CI/CD practices applied to data workflows (e.g., automated testing for pipelines, version-controlled data models)
- 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 (Product, Engineering, Sales, Compliance) 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
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