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We are seeking a highly skilled Data Platform Developer to join our team and help architect, build, and optimize our enterprise data platform. This role will focus on Snowflake as the core data warehouse technology and will be instrumental in designing scalable data models, defining semantic layers, and enabling advanced analytics and AI-driven use cases.
Job Responsibility:
Design and implement robust, scalable, and performant Snowflake database schemas and data models
Define and maintain semantic layers to support self-service analytics and machine learning workflows
Develop and optimize SQL for data transformation, aggregation, and consumption
Integrate data from diverse sources including relational databases, interface files, message queues, and APIs
Collaborate with data scientists, analysts, and application developers to ensure data accessibility and usability
Implement and maintain data governance, security, and RBAC policies within Snowflake
Monitor and tune performance of data pipelines and warehouse queries
Contribute to the development of data platform standards, best practices, and documentation
Requirements:
5+ years of experience in data engineering, database design, or data platform development
Strong expertise in Snowflake, including schema design, performance tuning, and data sharing
Proficiency in SQL, with experience writing complex queries and stored procedures
Experience with data integration from varied sources (e.g., APIs, flat files, message queues)
Familiarity with ETL/ELT frameworks and orchestration tools (e.g., dbt, Airflow)
Understanding of semantic modeling and analytics enablement
Solid programming skills in Python or Java for data processing and automation
Knowledge of data governance, security, and access control principles
Nice to have:
Experience with AI/ML workflows and enabling data access for model training and inference
Familiarity with cloud platforms (e.g., AWS, Azure, GCP) and cloud-native data services
Exposure to BI tools (e.g., Tableau, Power BI) and how they interact with semantic layers
Experience with CI/CD and DevOps practices in data engineering