Senior Data Engineer Production Support (Snowflake, dbt, Airflow)

YOUR ROLE

• Keep pipelines healthy: You monitor and support production data pipelines built on Airflow, dbt and PySpark, and resolve failures within agreed SLAs.
• Resolve incidents for good: You triage issues, run root-cause analysis and implement permanent fixes instead of repeating workarounds.
• Optimise Snowflake: You maintain and tune Snowflake queries, models and warehouses for performance, reliability and cost.
• Own on-call and alerting: You respond to alerts, take part in the on-call rotation and escalate and coordinate with other teams when needed.
• Serve our stakeholders: You handle data requests, bug reports and enhancements, prioritise by business impact and keep stakeholders updated until closure.
• Prevent the next incident: You improve monitoring, testing and data quality checks, and write runbooks and incident reports so knowledge is shared across the team.
• Be a role model in the project team: You pass on your way of working in daily collaboration, reviews and pairing.

YOUR PROFILE

• Engineering background: You bring 5+ years of experience as a Data Engineer, including production support, and know your way around Snowflake, dbt, PySpark and Airflow.
• Operations mindset: You are comfortable with incident management, root-cause analysis and SLA-driven support, and you debug DAG failures, retries and backfills with confidence.
• Stakeholder management: You manage expectations during incidents with timely updates and honest timelines, and you build trusted relationships with data, engineering and business teams.
• Communication: You explain technical issues and their business impact clearly to technical and non-technical audiences, and you write clear tickets and documentation.
• Nice to have: Experience with PagerDuty for alerting, on-call scheduling and escalation.
• Language skills: Strong verbal and written English.