Analytics Engineer

Role overview

Celigo is hiring an Analytics Engineer to own business logic and architect the company’s “Gold” data layer. You’ll transform raw data into clean, validated, high-performance tables, enabling a trusted “single source of truth” for executive reporting and decision-making across Product, Finance, and GTM.

Responsibilities

• Develop and maintain scalable data models using dbt / Coalesce to produce production-ready schemas
• Collaborate with Data Engineering and Data Analytics to ensure architecture supports business logic and reporting needs
• Implement automated testing, data documentation, and observability to ensure data trustworthiness
• Optimize SQL queries and warehouse configurations to improve performance and manage compute costs
• Maintain version control, CI/CD pipelines, and data-team coding standards
• Support the semantic layer and BI data catalogs to enable self-service analytics

Requirements

• Strong belief in applying software engineering best practices to data workflows (testing, versioning, peer review)
• Ability to design modular data models using Star Schema / Kimball methodologies
• Ability to communicate technical trade-offs to analysts and infrastructure engineers
• 3+ years in Analytics Engineering, Data Engineering, or a technical Data Analyst role
• Expert SQL skills for efficient, maintainable, readable code
• Hands-on experience with dbt / Coalesce and cloud data warehouses such as Snowflake or BigQuery
• Familiarity with Git, pull request workflows, and command-line interfaces
• Degree in a quantitative field such as Computer Science, Math, or Statistics

Nice to have

• Python experience for data orchestration (e.g., Airflow) or advanced data manipulation
• Knowledge of fintech or SaaS metrics (e.g., ARR, churn, financial reconciliation)

Compensation

• Expected base salary: $120,000–$140,000 per year (actual depends on skills, experience, and location). Variable incentives and benefits may be included in a formal offer.