Senior Snowflake Data Engineer

About the role

We are seeking a Senior Data Engineer to help build and scale a modern cloud data platform that powers analytics, reporting, machine learning, and future AI initiatives.

Responsibilities

• Design, develop, and maintain scalable DBT models and analytics-ready datasets.
• Build and maintain reusable dimensional, semantic, and enterprise data models.
• Write and optimize complex SQL transformations across large datasets.
• Develop Python-based tools for data quality, automation, validation, and platform operations.
• Own data products and pipelines from design through production support.
• Implement data quality checks, documentation, lineage, monitoring, and observability standards.
• Partner with stakeholders to define KPIs, metrics, business definitions, and trusted data assets.
• Support data governance initiatives, including metadata, ownership, stewardship, and certification.
• Help prepare enterprise data assets for future AI, machine learning, and advanced analytics use cases.

Requirements

• 7+ years of experience in Data Engineering, Analytics Engineering, Software Engineering, or a related field.
• Strong SQL experience, including complex analytical transformations at scale.
• Hands-on DBT experience, including modeling, testing, documentation, CI/CD, and deployment workflows.
• Strong Python programming skills for data processing, automation, APIs, and tooling.
• Experience designing dimensional, semantic, and analytics-focused data models.
• Experience building and optimizing large-scale data pipelines and cloud-based data platforms.
• Strong understanding of modern ELT practices and data warehouse architecture.
• Experience with Git-based development workflows and code review processes.
• Experience supporting BI, analytics, and self-service reporting environments.
• Experience supporting production data environments, incident response, and operational troubleshooting.
• Bachelor’s degree in Computer Science, Data Engineering, Information Systems, Data Science, or a related field, or equivalent practical experience.

Preferences

• Experience with Snowflake, AWS, Airflow or Astronomer, Fivetran, RudderStack, GitHub, and modern BI platforms.
• Experience with data governance tools such as Atlan, Collibra, or similar platforms.
• Familiarity with metadata management, lineage, stewardship, and enterprise data quality practices.
• Experience defining business metrics, KPI standards, and enterprise data definitions.
• Exposure to AWS services such as S3, RDS, Lambda, or related cloud storage and processing technologies.
• Interest in AI-enabled analytics, semantic layers, retrieval-based architectures, AI agents, or intelligent automation.