Architect & Build - Play a key role in shaping the strategic vision and providing technical leadership for a major greenfield effort to rebuild and modernize our data warehouse platform.
Solve Problems - Address complex data engineering challenges proactively, applying innovative solutions that enhance performance, resilience, and scalability.
Collaborate - Participate actively in agile practices, contributing within crossfunctional squads that dynamically address evolving data engineering needs across the organization.
Secure - Ensure rigorous adherence to best practices in data governance, security, compliance, and information integrity.
Engage - Collaborate closely with internal teams and stakeholders to facilitate successful adoption and understanding of data initiatives and solutions.
Lead & Mentor - Serve as a mentor to a team of engaged and curious engineers, actively guiding and leveling up the team's technical skills and capabilities.

5 years of experience in software or data engineering or related fields
Demonstrated capability in supporting the architectural design and ongoing operation of large-scale data warehouse systems leveraging as-code orchestration frameworks such as Airflow or Dagster
Experience with modern data warehousing solutions (eg, Fabric, Snowflake, Databricks)
Advanced experience in SQL for modelling, optimization, and analytics workloads
Familiarity with analytics, Business Intelligence tools, or data visualization platforms
Solid expertise in Python and modern open-source data engineering tools, including Spark, Parquet, and dbt
Comfortable building scalable cloud-native systems using containerization and orchestration technologies Docker, Kubernetes, etc.)
Familiarity with essential DevOps practices, including version control, automated CI/CD, etc.
A deep passion for technical mentorship and knowledge sharing
Bonus: Experience with REST APIs, GraphQL/OData and Event-Driven Architecture

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