Top Analytics Engineer Jobs in NYC, NY

The Analytics Engineer will develop data pipelines, optimize data models, create dashboards in BI tools, and collaborate with stakeholders for data-driven insights.

Lead design and optimization of analytics products and Tableau dashboards, manage and tune reporting data pipelines (Redshift/ETL), implement performance best practices, collaborate cross-functionally, and drive automation and AI opportunities to improve reporting and analytics for healthcare customers.

The Analytics Engineer will design and maintain analytical data models, ensure data pipeline reliability, and collaborate with stakeholders to meet data needs. Responsibilities include data documentation, investigation of discrepancies, and contribution to AI data initiatives.

The Analytics Engineer will design data models, maintain analytics pipelines, document data governance, and partner with stakeholders to address data needs.

The Analytics Engineer will develop and maintain analytical data models, manage ELT pipelines, document data governance, and partner with stakeholders to meet their data needs.

The Senior Data Engineer will design and implement scalable data models in BigQuery using dbt for analytics and reporting, ensuring data governance and optimal performance.

As an Analytics Engineer, you'll own analytics solutions from data architecture to visualization, ensuring streamlined insights for business stakeholders.

The Enterprise Performance Analytics Engineer builds and maintains data pipelines and models, ensuring data quality and efficient reporting for analytics teams.

As an Analytics Engineer at Axios, you'll design and maintain data products and visualizations, improving decision-making through actionable insights.

As a Staff Analytics Engineer, you'll design and maintain a robust analytics data layer, ensuring accuracy in R&D data and mentoring team members.

As a Data Analytics Engineer I, you'll bridge engineering and analytics, manage data pipelines, collaborate with stakeholders, and utilize modern open-source tech for data transformation and integration in structured finance.

The RevOps Analytics Engineer is responsible for maintaining data infrastructure, building reliable data systems, and supporting revenue analytics through effective data modeling and ETL/ELT processes.

The Analytics Engineer will design and maintain data infrastructure for business intelligence, optimize analytics processes, and ensure data quality and governance.

The Senior Data Analytics Engineer will own the data ecosystem, manage pipelines, support AI/ML initiatives, and translate business goals into technical requirements. They will also ensure data reliability and optimize performance across analytics platforms.

The Analytics Engineer at Seeq will work as a technical advisor, leading customer engagements, designing and implementing analytics solutions, and providing industry expertise to optimize industrial processes.

The Analytics Engineer will build data models and pipelines for reporting and analytics, improving data infrastructure for ML and AI products, and setting processes for data collection and analysis.

The Digital Marketing Analytics Engineer handles data systems, analytics, and reporting for clients, transforming complex data into actionable insights while collaborating with marketing teams.

The Staff Analytics Engineer will enhance the analytics data layer, improve data quality, maintain core data models, and introduce AI-assisted workflows to optimize insights generation.

As a Software Engineer, you'll develop and enhance core analytics libraries using C++ and Python, collaborate with quants and traders, and ensure high-quality software delivery.

As an Analytics Engineer, you will create scalable solutions for data reporting, build data pipelines, and establish high data integrity standards while collaborating with multiple teams.

The Analytics Engineer will enhance BI infrastructure, collaborate with Data Engineering, and deliver analytics-ready data. Responsibilities include managing Snowflake, dbt projects, and CI/CD workflows, optimizing data structures, and supporting BI initiatives.

The Principal Analytics Engineer will design and engineer a data infrastructure to support AI-powered insights and reporting for Elastic's marketing strategies, ensuring data quality and usability for all stakeholders.

As a Business Intelligence and Analytics Engineer, you will develop data tools, ensure data quality, deliver analytical insights, and collaborate with cross-functional teams to empower data-driven decision-making.

As a Senior Data Analytics Engineer, you will build and manage data pipelines, support AI/ML initiatives, and ensure data reliability and accessibility within the organization.

As a Senior Software Engineer, you will develop parallel algorithms for data processing, optimize C++ and CUDA code, and contribute to open-source projects.