Collaborate & Strategize: Partner closely with business stakeholders to understand their challenges and design end-to-end architecture that solves complex business problems.
Build & Maintain Data Models: Design, develop, and own robust, efficient, and scalable data models in Snowflake and Iceberg using dbt and advanced SQL.
Orchestrate & Automate: Build and manage reliable data pipelines and CI/CD workflows using tools like Airflow, Python, and Terraform to ensure data is fresh, trustworthy, and infrastructure is version-controlled.
Champion Data Quality: Implement rigorous testing, documentation, and data governance practices to maintain a single source of truth.
Enable Analytics & Workflows: Act as the Product Owner and Tech Lead for your data domains, taking responsibility for the end-to-end data product delivery– from raw ingestion to data models enabling analytics and data apps in tools like Tableau and Retool.
Innovate with AI: Help us build our next-generation data infrastructure by integrating AI capabilities (like Snowflake Cortex AI) to democratize analytics and empower the business.
Architect Observability: Implement monitoring and alerting frameworks (e.g., dbt packages or Monte Carlo monitors) to proactively catch "silent" data failures before stakeholders do.

6+ years of experience in Analytics Engineering, Data Engineering, or a similar role.
Deep expertise in SQL and developing complex data models for analytical purposes (e.g., dimensional modeling).
Hands-on experience with:
Data Warehousing: High proficiency in Snowflake (preferred) and experience with Open Table Formats like Iceberg.
Data Transformation: dbt
Orchestration & ETL: Airflow, Fivetran, Airbyte
Cloud Platform: AWS
Programming/Ingestion: Python
Infrastructure as Code: Terraform
AI-Augmented Development: Proficiency using AI coding assistants (Cursor, Copilot, or Claude) to accelerate development and automate routine tasks.
A strong analytical mindset with a proven ability to solve ambiguous business problems with data.
Excellent communication skills and experience working cross-functionally.
Self-starter with the ability to self-project manage work
A user focus with the ability to understand how a data consumer will use the data products you build

Data Engineer

Key skills