Data Engineer

About the Role

We are seeking a visionary Data Architect for our Customer Success Analytics team within Autodesk's Customer Success division. As the technical cornerstone, you will design and build foundational data infrastructure, transforming disparate sources into a single source of truth to drive retention and growth insights.

Key Responsibilities

• Data Strategy & Architecture: Architect an automated, resilient Snowflake environment moving from manual processes to scalable warehouses. Optimize performance, cost, and governance.
• Modeling & Transformation: Design dimensional data models consolidating internal/external logic using dbt (data build tool) with rigorous testing and version control.
• Pipeline Orchestration: Manage end-to-end pipelines in Python and orchestrate workflows via Airflow for reliable downstream delivery.
• Governance & Quality: Establish frameworks for data quality monitoring, lineage tracking, and naming standards to ensure metric accuracy.
• Maintenance & Mentoring: Refactor legacy code into modern architectures. Mentor teams on SQL best practices (CTEs, window functions), modeling techniques, and engineering standards via Git/CI-CD processes.

Qualifications

Minimum Requirements:

• 8+ years in Data Architecture, Engineering, or BI.
• Expert Snowflake proficiency (performance tuning, cost optimization).
• Hands-on experience with the modern data stack: dbt and Python scripting/automation.
• Strong workflow orchestration skills (Airflow) and Git-based CI-CD workflows.
• Experience integrating data structures with BI tools like Power BI or Tableau.

Ideal Candidate Profile:

The ideal candidate is a self-starter 'builder' who thrives on creating structure from ambiguity. You possess deep cloud data warehousing knowledge, a passion for clean code, and the ability to bridge technical complexity with business value (SaaS metrics like Retention/Churn).