Data Engineer

Celigo is looking for a Data Engineer to contribute to the development, scaling, and maintenance of our Snowflake-based data ecosystem. You will implement and deliver scalable ELT pipelines, production-grade data models, and the observability frameworks that keep them reliable, translating business requirements into well-documented, high-performance data solutions that power analytics, BI, and ML across the organization. Partnering closely with Analytics, Product, and Engineering, you will help enforce data quality standards, align with governance practices, and continuously optimize for cost efficiency and data freshness.

Responsibilities

Design, build, and maintain scalable ELT/ETL pipelines and data infrastructure using Snowflake and modern tooling; Implement data models, including dimensional, data vault, and medallion/lakehouse patterns, to support analytics, BI, and ML use cases; Collaborate in architectural discussion and decision making with the team; 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

Requirements

Strong hands-on experience with Snowflake, including performance optimization, warehouse configuration, access controls, and cost-efficient development practices; 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)

Benefits

Remote-first culture, built on trust, collaboration, and transparency; High-growth, inclusive work environment; Lightspeed learning opportunities; Three weeks of vacation (starting year one); Wellness days and holidays to recharge; Parental leave and a generous benefits package; Monthly tech stipend; Recognition and career development opportunities; Competitive compensation and benefits