Celigo
AnalyticsEngineer
Neural analysis suggests this role is
optimal for Mid candidates.
“Analytics Engineer at Celigo. Skills: SQL, dbt, Data Modeling. Develop scalable data models using dbt / Coalesce. Transform raw data into clean schemas”
What You'll Achieve.
Ensure data warehouse is a trusted single source of truth; Empower company with reliable data; Drive decisions across Product, Finance, and GTM teams
Industry & Context.
Transforming complex datasets; Optimize SQL queries; Optimize warehouse configurations
What They're Looking For.
Must Have
Degree in Computer Science, Mathematics, Statistics, or a related quantitative field, 3+ years of experience in Analytics Engineering, Data Engineering, or a technical Data Analyst role, Expert-level proficiency in SQL, Hands-on experience with dbt / Coalesce, Hands-on experience with modern cloud data warehouses like Snowflake or BigQuery, Familiarity with Git, Familiarity with pull request workflows, Familiarity with command-line interfaces
Nice to Have
Experience with Python for data orchestration, Experience with Airflow, Experience with advanced data manipulation, Understanding of Fintech or SaaS-specific metrics, Understanding of ARR, Understanding of churn, Understanding of financial reconciliation
What You'll Do.
Develop scalable data models using dbt / Coalesce
Transform raw data into clean schemas
Implement automated testing
Implement data documentation
Implement observability frameworks
Optimize warehouse configurations
Maintain version control workflows
Maintain CI/CD pipelines
Support semantic layer
Support BI data catalogs
How You'll Work.
Team & Collaboration
Collaborate with Data Engineering; Collaborate with Data Analytics; Communicate technical trade-offs to analysts; Communicate technical trade-offs to infrastructure engineers
Communication Scope
Communicating technical trade-offs
Full Job Description
Integration meets Innovation At Celigo, we believe integration should empower — not exhaust — innovation. As a modern Integration and Automation Platform (iPaaS), we’re on a mission to simplify how companies integrate, automate, and optimize processes. Powered by game-changing technology like runtime AI and prebuilt, mission-critical integrations, Celigo is redefining how businesses connect their world. Celigo is looking for an Analytics Engineer to serve as the definitive owner of our business logic and the primary architect of our "Gold" data layer. You will bridge the gap between raw data and executive-level insights by transforming complex datasets into clean, validated, and highly performant tables. By applying software engineering rigors—such as version control, automated testing, and CI/CD—to our workflows, you will ensure our data warehouse remains a trusted "single source of truth." Your mission is to empower the company with the reliable data to drive decisions across Product, Finance, and GTM teams. What would you do if hired? Develop and maintain scalable data models using dbt / Coalesce to transform raw data into clean, documented, and production-ready schemas. Collaborate with Data Engineering and Data Analytics to ensure technical architecture supports business logic and reporting requirements. Implement automated testing, data documentation, and observability frameworks to ensure a "single source of truth." Optimize SQL queries and warehouse configurations to improve performance and manage compute costs. Maintain version control workflows, CI/CD pipelines, and coding standards across the data team. Support the semantic layer and BI data catalogs to enable self-service exploration. Who are we looking for? Skills & Abilities Strong belief in applying software engineering best practices (testing, versioning, peer review) to data workflows. Ability to design modular data models (Star Schema, Kimball) that balance flexibility with system performance. Prof
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