Data Engineer

• Strong understanding of data validation, testing (e.g., dbt tests), and lineage tracking.
• Emphasis on maintaining data trust across pipelines and models.

• Partner with business and technical stakeholders to define data needs and deliver insights.
• Ability to explain complex data concepts in clear, non-technical terms.

• Maintain clear documentation for models, metrics, and data transformations (using DBT docs or similar).
• Strong verbal and written communication skills; able to work cross-functionally across teams.

• Proactive in identifying and resolving data gaps or issues.
• Self-starter with a continuous improvement mindset and a focus on delivering business value through data.

• deploy scalable, secure, and high-performing Snowflake environments in line with data governance and security in palce using Terraform and other automation scripit
• Automate infrastructure provisioning, testing, and deployment for seamless operations.

Requirements

• Strong SQL & DBT Expertise
• Experience building and maintaining scalable data models in DBT .
• Proficient in modular SQL , Jinja templating , testing strategies, and DBT best practices.
• Data Warehouse Proficiency
• Hands-on experience with Snowflake including:
• Dimensional and data vault modeling (star/snowflake schemas)
• Performance optimization and query tuning
• Role-based access and security management
• Data Pipeline & Integration Tools
• Experience with Kafka (or similar event streaming tools) for ingesting real-time data.
• Familiarity with SnapLogic for ETL/ELT workflow design, orchestration, and monitoring.
• Version Control & Automation
• Proficient in Git and GitHub for code versioning and collaboration.
• Experience with GitHub Actions or other CI/CD tools to automate DBT model testing, deployment, and documentation updates.