Top Senior Data Engineer Jobs in NYC, NY

The Principal Database Architect & Engineer will own the data components of complex infrastructure solutions and lead teams to deliver innovative database technology solutions, ensuring optimal performance and operational efficiency.

The Data Engineer will build scalable privacy-centric data frameworks, engineer data pipelines, and ensure compliance with privacy regulations at Netflix.

As a Senior Data Engineer, you will enhance the data lakehouse, optimize data workloads, perform complex transformations, and develop frameworks to improve delivery velocity, focusing on cybersecurity solutions.

Seeking a Data Engineer to design and maintain ETL processes, oversee data warehouse operations, and collaborate across teams to enhance data accessibility and accuracy.

The Senior Data Engineer will design and maintain data warehouse infrastructure, develop ELT pipelines, ensure data security, and lead analytics collaborations.

The Senior Data Engineer designs and maintains data pipelines and structures, implements Adobe tools, validates data accuracy, and collaborates with teams for data-driven insights.

The Senior Data Engineer will improve data platforms, implement best practices, and lead initiatives across business teams using various cloud and big data technologies.

As a Senior Data Engineer, you will build data pipelines, improve the data engineering stack, and maintain a data warehouse for analytics. You'll collaborate with teams to ensure data accuracy and contribute to system reliability.

The Senior Data Engineer will design and build scalable data pipelines and models, ensuring data quality and optimizing data infrastructure using AWS and Snowflake. Responsibilities include leading projects, integrating APIs, and collaborating across teams to enhance data products for value-based care.

The Staff Data Engineer will design and implement data warehousing solutions, lead design discussions, mentor engineers, and tackle complex data challenges while ensuring data quality and insights delivery.

As a Senior Data Engineer, you will build and maintain data pipelines for analytics, collaborating with teams to implement data models and ensure data quality.

As a Senior Data Engineer, you will design and build data products, establish best practices, and lead technical initiatives in data architecture and workflows within the single-family rental industry.

As a Senior Data Engineer, you will design robust ETL processes, maintain data infrastructure, and collaborate to optimize data access and analytics.

The Senior Data Engineer will develop data pipelines for predictive modeling, collaborate with teams, manage data assets, and apply AI solutions in an insurance context.

Lead the design of DataOps platforms, focusing on scalable data infrastructures and automation frameworks. Oversee robust data orchestration and establish quality frameworks.

As a Senior Data Engineer, you'll design and implement a Snowflake-centric data architecture, operationalize ML and LLM processes, and enable advanced analytics while collaborating with cross-functional teams.

Design, build, and maintain scalable data infrastructure in the cloud using AWS services and Infrastructure as Code to ensure data reliability and performance.

The Senior Data Engineer will manage and transform data pipelines, implement changes in Snowflake, monitor costs, and resolve data issues.

The Data & Analytics Engineer will model and serve data, improve architecture, and collaborate with teams to sustain the data strategy, requiring 5+ years of experience.

The role involves building and optimizing data pipelines, modeling datasets, applying machine learning techniques, and supporting data strategies. Candidates should have experience with Python, data lakes, warehousing, and related technologies.

As a Senior Data Engineer, you'll design, build, and optimize data infrastructure while collaborating with teams to enhance data flow and integration across platforms.

The role involves building and optimizing data pipelines, managing data integration, supporting analytics, and collaborating with cross-functional teams to enable data-driven decisions.

Design and maintain high-quality data pipelines, develop DBT models, collaborate with analytics and data science teams, and optimize data operations for scalability.