Analytics Engineer - NYC Data Foundation & Dashboards

Amadeus Search; New York, Northern (NY, KY); Hybrid; USD 150,000 - 200,000; Full time

Benefits offered by this job

Fully covered medical, dental, and视觉

Unlimited PTO and 16 weeks paid Par?al

401(k), FSA, commuter benefits

Daily lunch provided at the office

Job summary

Amadeus Search is hiring an Analytics Engineer for an on-site role in New York. You will design and maintain the data foundation, ensure decision-grade data availability, and own data transformations, dashboards, and analytics tooling.

You will build data models, manage pipelines, and standardize metrics while collaborating with product, ops, and leadership. Expect ownership, cross-functional impact, and a fast-paced startup environment.

Qualifications

• Experience as an analytics engineer or data engineer in a high-growth environment.
• Proficiency in SQL and Python, with experience using modern data tools (e.g., dbt, Fivetran, Airflow).
• Familiarity with GCP BigQuery or similar cloud-based data warehouses.

Responsibilities

• Build and maintain core data models to support internal analytics and external reporting.
• Design and manage pipelines that convert raw data into analytics-ready formats.
• Create dashboards and reporting tools used by product, ops, and go-to-market teams.
• Standardize metrics definitions and ensure cross-team consistency.
• Improve and scale the analytics infrastructure using tools like BigQuery, Dataform, and Fivetran.
• Collaborate with cross-functional stakeholders to translate business needs into data systems.
• Contribute to data governance, documentation, and internal analytics best practices.

Skills

SQL

Python

dbt

Fivetran

Airflow

BigQuery

Tools

dbt

Fivetran

Airflow

BigQuery

Job description

Amadeus Search is hiring an Analytics Engineer for an on-site role in New York. You will design and maintain the data foundation, ensure decision-grade data availability, and own data transformations, dashboards, and analytics tooling.

You will build data models, manage pipelines, and standardize metrics while collaborating with product, ops, and leadership. Expect ownership, cross-functional impact, and a fast-paced startup environment.