Top Data Engineer Jobs in NYC, NY

As a Senior Data Engineer, you will design and maintain data pipelines, define governance standards, and collaborate across teams to enhance Headway’s data architecture.

Develop and productionize a next-gen Dispatch System, build predictive models, automate processes, and lead a small team in optimizing operations.

The Data Engineer will design and maintain scalable data pipelines, integrate APIs, support ML teams, and optimize data systems for performance and reliability.

The Data Engineer will design and maintain ETL pipelines and data storage solutions, collaborating with cross-functional teams to ensure efficient data processing and delivery.

The Lead, Data Engineer leads the data engineering team, designing scalable data solutions, mentoring staff, and ensuring data quality while collaborating with stakeholders to meet business goals.

As a Data Engineer II, you will build and maintain ETL pipelines, analyze requirements, and mentor junior colleagues while supporting customer implementations.

The Data Engineer will develop Python data applications, collaborate with teams to optimize data solutions, and maintain production operations support.

The Senior Data Engineer will build and maintain data pipelines, optimize data processes, design a data validation framework, and ensure user privacy and security.

The candidate will improve the data ETL pipeline, build analytical tools, manage operations, and expand into new markets and asset classes.

As a Data Engineer, you will build and optimize data pipelines, manage ETL workflows, and ensure efficient data access and quality within the infrastructure.

Design and deploy data processing pipelines, analyze data to extract insights, and develop software systems for data management and privacy.

The Data Engineer will create scalable analytics solutions, manage data integrations, report on marketing performance, and develop pipelines using various technologies.

The role involves interacting with Solana nodes, building data pipelines to ClickHouse, designing dashboards, maintaining data accuracy, and responding to on-chain incidents.

As a Data Engineer, you will build data solutions for trading, ensuring data quality and collaborating with researchers to support decision-making.

The Data Architect designs data flows, defines standards, ensures data quality, and collaborates on data strategies while integrating advanced technologies.

The Data Engineer will build ETL pipelines and data infrastructure, ensure data quality, and implement modern data warehousing for analytics improvements, while collaborating with stakeholders across teams.

The Senior Data Engineer will build and maintain data pipelines, work with cross-functional teams, and optimize performance using various data processing tools.

The role involves building and improving data engineering solutions, designing ETL/ELT pipelines, and working with data modeling, warehousing, and cloud platforms to support influencer marketing at Influur.

The Data Engineer will maintain and optimize data pipelines, manage infrastructure, support ML workflows, and collaborate with teams on data products.

This role involves building and maintaining data pipelines, developing data models, and ensuring data discoverability while enabling scalable analytics on blockchain data.

The Senior AI Data Engineer will design and maintain datasets for AI models in cybersecurity, ensuring data quality and relevance while collaborating with teams.

As a Data Engineer, you will design and implement a data platform, maintain data pipelines, work with Airflow and BigQuery, and ensure data compliance while collaborating with teams.

As a Data Engineer, you'll design and maintain data platforms, develop data pipelines, collaborate with teams, and ensure data quality for diverse stakeholders.

As a Data Engineer Apprentice, you will maintain data pipelines, automate workflows, and collaborate on projects while completing the AI and Machine Learning bootcamp.

The Senior Data Engineer will maintain ChowNow's data platform, enhance data pipelines, work with data scientists, and improve data quality and accessibility, contributing to executive decision-making and business growth.