Top Data Engineer Jobs in NYC, NY

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

As a Senior Data Engineer, you will design, develop, and implement data solutions, utilizing cloud technologies and collaborating with teams to support technical solutions and mentor others.

The Junior Data Engineer will analyze data, build and maintain data pipelines, support CI/CD processes, and assist in IT modernization efforts for a Federal client.

The Senior Data Engineer will manage data flow and ensure accuracy, improve data engineering stacks, build and maintain analytics warehouses, and support stakeholders with data solutions while participating in system reliability on-call rotations.

The Founding Data Engineer/Data Scientist will design and build data systems for payments and fraud, ensuring data accuracy and enabling analytics. Responsibilities include establishing data pipelines, models, quality checks, and documenting processes while collaborating with stakeholders.

As an FP&A Data Engineer, you will manage data pipelines, develop financial models, and automate reporting to assist management and teams in making data-driven decisions.

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

The role involves owning the data infrastructure and pipeline, building robust data pipelines, managing Snowflake and dbt, and delivering analytics and dashboards.

The Data Engineer designs and builds AI-driven solutions, optimizes data pipelines, manages integrations, and enhances analytics capabilities across the organization to improve efficiency and decision-making.

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

The Principal Data Engineer will design and evolve data architecture, build data transformation workflows, and ensure integration of diverse data sources while enabling AI and analytics capabilities.

Lead design and delivery of enterprise data centralization and automation for reporting and BI. Build and maintain ETL/SSIS pipelines, data orchestration, file delivery and quality controls, follow SDLC/agile, mentor junior engineers, and partner with business stakeholders to capture requirements and ensure timely data delivery.

Design, build, and maintain scalable ETL/ELT data pipelines on Databricks and AWS S3; manage large geospatial and temporal datasets; productionize ML models; implement data validation, testing, and monitoring; optimize storage and processing; document workflows; collaborate cross-functionally.

Design, implement, optimize, and maintain scalable, high-availability database solutions for a SaaS healthcare product. Integrate client data, resolve complex data issues, refactor systems for Azure, optimize MSSQL performance, participate in code reviews, and deliver features within Agile/Scrum to ensure reliable, high-performance data services.

As a Data Engineer at LiveKit, you will manage the analytics infrastructure, develop scalable GCP-based data pipelines, and ensure effective data movement and transformation processes, while collaborating with the Analytics and engineering teams.

The Data Engineer Senior will optimize data pipelines, work within scrum teams, mentor others, and improve data quality, reliability, and governance.

The Data Engineer will build and scale data systems, manage data pipelines, ensure data quality, and collaborate with cross-functional teams to utilize entertainment data effectively.

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.

Build and maintain cloud data pipelines and ML feature/model workflows in Snowflake and AWS. Implement data ingestion, transformations, quality checks, monitoring, and documentation. Collaborate with data scientists, analysts, and product teams to support analytics, audience insights, rapid prototyping, and reliable production deployments.

Design, build, and maintain ELT pipelines and analytics-ready data models to support reporting, KPIs, and downstream ML use cases; implement data quality, optimize pipeline performance, document lineage, and ensure governance and privacy.

The Data Engineer will build and optimize data pipelines and infrastructure, ensuring data quality for analytics and machine learning initiatives while collaborating with teams to develop data solutions.

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 Senior Data Engineer will design, build, and maintain scalable party data solutions, integrating cloud-native platforms and improving legacy systems while mentoring junior engineers.

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

The Data Engineer will design and optimize ETL pipelines, integrate data, ensure data quality, and troubleshoot issues, enabling decision-making across the organization.