Senior Data Engineer

Celigo is an intelligent automation and Integration Platform as a Service (iPaaS) company that simplifies how businesses integrate, automate, and optimize processes. The Senior Data Engineer will architect and steward the Snowflake-based data ecosystem by building scalable ELT pipelines, production-grade data models, and observability frameworks that support analytics, BI, and ML. The role also partners with cross-functional teams to ensure data quality, governance, performance, cost efficiency, and freshness.

Responsibilities:

• Design, build, and maintain scalable ELT/ETL pipelines and data infrastructure using Snowflake and modern tooling
• Architect and implement data models — including dimensional, data vault, and medallion/lakehouse patterns — to support analytics, BI, and ML use cases
• Collaborate with Analytics, Product, and Engineering teams to translate business requirements into reliable, well-documented data solutions
• Establish and enforce data quality standards, automated validations, and observability frameworks to ensure high reliability across all pipelines
• Contribute to data governance practices, including documentation, data lineage, access control, and compliance standards
• Monitor and optimize pipeline performance, compute cost efficiency, and data freshness across the warehouse
• Evaluate and implement emerging Snowflake features and data tooling to improve engineering velocity and reduce costs
• Leverage AI-assisted development tools (e.g., Claude Code, GitHub Copilot, Cursor, or equivalent) to accelerate pipeline development, code review, and documentation
• Participate in code reviews, architectural discussions, and cross-functional technical planning sessions

Requirements:

• Deep expertise in Snowflake architecture, including virtual warehouse configuration, clustering, data sharing, role-based access control, and cost governance
• Strong command of modern ELT tooling such as dbt, Fivetran, Airflow, or Prefect in a Snowflake-native environment
• Hands-on experience integrating AI/ML tools into the development cycle, including AI-assisted coding, automated testing, or LLM-powered data workflows
• Proven ability to translate complex business requirements into scalable, well-documented technical solutions
• Strong communication skills with the ability to collaborate effectively across technical and non-technical teams
• Degree in Computer Science, Engineering, or a related technical field
• 5+ years of hands-on experience in data engineering, specifically building production-grade pipelines and distributed computing frameworks
• 3+ years working directly with Snowflake in a production capacity
• Demonstrated experience in architecting or contributing to at least one full data warehouse migration or rebuild on Snowflake
• Advanced proficiency in SQL and at least one programming language (Python preferred)
• Experience with version-controlled, CI/CD-driven data pipeline development (e.g., dbt + GitHub Actions or equivalent)
• Familiarity with data governance, security, and compliance considerations in a cloud data warehouse context (e.g., column-level security, dynamic data masking, audit logging)