Data Operations Engineer / 3rd level support
Popis pozície
As a Data Operations Engineer, you will be the guardian of our live data ecosystem. You’ll bridge the gap between development and production, ensuring our data products—built on Snowflake, DBT, and Streamlit—are resilient, scalable, and high-performing. You aren’t just "fixing" things; you’re optimizing the backbone of our business intelligence.
Key Responsibilities
Operational Excellence: Own 2nd and 3rd-level support for our core data stack (Snowflake, DBT, Streamlit, and Power BI), ensuring maximum uptime and data integrity.
Collaborative Development: Partner with Delivery Teams to architect new solutions and deploy major enhancements to existing data products.
Incident Mastery: Lead root-cause analysis (RCA) for complex incidents, managing everything from quick-fix patches to strategic configuration updates.
Observability & Monitoring: Proactively track system health and KPIs. You will design and maintain the alerts, dashboards, and SLA/SLO frameworks that keep us ahead of potential failures.
Governance & Lifecycle: Manage the "boring but critical" stuff—documentation, access controls, and lifecycle planning—to ensure our environment stays secure and compliant.
Cross-Functional Bridge: Act as the technical translator between Engineering, Architecture, and Business stakeholders during incidents and change management cycles.
Requirements
The Core: Deep, hands-on expertise in Snowflake and DBT (specifically operational workflows and SQL optimization).
The Toolbox: Proficiency in Python or SQL for automation and integration; familiarity with JavaScript is a plus.
Data Architecture: A solid grasp of modern ELT patterns, data-product lifecycles, and CI/CD pipelines.
Visualization & Health: Experience building or using monitoring tools via Snowflake dashboards, Power BI, or custom Streamlit applications.
The Mindset: You possess a "Product Ownership" mentality. You don’t just close tickets; you improve the system so the problem doesn't happen twice.
