New York, NY
Analytics Engineer
Analytics Engineer jobs in New York, NY
$100K – $212K
Typical pay · from 4 of 5 jobs
Updated 4 Nov
About these jobs CrowdStrike, Genius AI and Independence Pet Group are hiring Analytics Engineers in New York, NY. Typical pay runs $113K to $215K. Most roles are hybrid, and many are remote. Employers ask for 2-5 or 5-10 years of experience plus SQL, Python and Snowflake.
Analytics Engineer
Kula Example
The Analytics Engineer will lead the development of data analytics solutions and maintain dbt models to ensure data accuracy and actionable insights. They will collaborate with cross-functional stakeholders to define KPIs and integrate machine learning models into scalable data solutions.

Analytics Engineer
Rippling · Software Development · 7.9k people
You will design and maintain services to process financial data while collaborating with cross-functional teams to ensure accurate settlement and reporting. Additionally, you will build full-cycle analyses, develop real-time dashboards, and automate reconciliation processes to support financial operations.
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Senior Analytics Engineer
Independence Pet Group · Insurance · 638 people
The Analytics Engineer will own the analytics engineering process, building and optimizing data pipelines and architecture to transform raw data into reliable, analytics-ready models. They will partner with cross-functional teams to define KPIs, implement data quality standards, and ensure scalable data delivery.

Sr. Analytics Data Platform Engineer
DoubleVerify · Software Development · 34 people
Design and maintain a contract-driven data platform that automates the deployment of pipelines to Snowflake, Airflow, and Looker. Lead initiatives to integrate social platform data and mentor a team of software engineers to ensure high-quality, scalable data solutions.

Senior Analytics Engineer, AI & DX Analytics
Block · Software Development · 6.2k people
Instrument and capture engineering and AI telemetry, partner on production data pipelines, and define trustworthy metrics for AI investment and developer experience. Build executive-facing dashboards and analyses, communicate recommendations to senior stakeholders, and identify opportunities to improve AI ROI and developer productivity.
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