Top Data Engineer Jobs in NYC, NY

As a Data Engineer, you will design, implement, and maintain data systems for Notifications at Whatnot, ensuring data quality and performance while collaborating with cross-functional teams on data architecture and workflows.

Summer internship focused on building scalable data architectures and pipelines, automating data processes, improving data quality frameworks, and supporting cloud infrastructure. Work includes AWS automation, data warehousing, workflow optimization, platform integration, and operationalizing tools to process structured and unstructured data while leveraging analytics, AI/ML, and standardized pipelines.

Lead technical strategy and architectural evolution in marketing technology, mentoring teams and driving innovative solutions across data engineering and platforms.

Lead design and implementation of data architecture, ETL/ELT pipelines, data models, warehouses and lakes. Ensure data governance, security, cloud deployments, performance and cost optimization. Coach and manage team members, partner with stakeholders, and drive data-driven solutions for clients.

Lead design and implementation of enterprise data architecture and cloud-based data solutions. Manage large data engineering projects, develop data models and pipelines, ensure governance and security compliance, advise clients strategically, and build high-performing inclusive teams.

Design and implement data architecture and scalable ETL/ELT pipelines on cloud platforms (AWS/Azure/GCP). Analyze complex problems, mentor junior staff, ensure data governance/security compliance, liaise with stakeholders, and deliver high-quality client solutions while developing technical and client-facing skills.

Design and build data infrastructure and pipelines using cloud and big-data tools. Develop data lakes/warehouses, ensure data quality and security, collaborate with clients, and apply data architecture, transformation, and analytics to deliver insights.

The Data Engineer II will build and optimize data pipelines, develop reusable data sets, and ensure data integrity and security.

As a Data Engineer, you'll lead data engineering projects, develop data transformations, build workflows with Apache Airflow, and ensure data quality and integrity while collaborating with stakeholders.

The Data Engineer will design and build scalable data systems, contribute to the architecture of the data platform, and collaborate with AI/ML engineers to enhance automation and intelligence in Canoe's systems.

The Principal Data Engineer at NBCUniversal leads the development of data applications, manages data pipelines, and collaborates with teams while coaching junior engineers. Responsibilities include designing scalable data solutions and integrating AI technologies.

Build, model, and maintain scalable BigQuery-based data solutions on GCP. Implement performant data models, storage partitioning/clustering, ETL improvements, data validation, and documentation. Collaborate with architects, data scientists, and engineers to deliver governed, high-quality data for reporting and AI initiatives.

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.

Own and evolve the data lake and analytics stack powering fleet observability. Build and maintain scalable ETL/ELT pipelines, operate data lake infrastructure (Iceberg, Trino, Airflow, Spark, Superset), produce analytics and executive reporting, create dashboards and runbooks, and implement data governance and observability.

Lead architecture and evolution of Headway's data platform (warehouse, ingestion, orchestration, CI/CD, monitoring, cloud infra). Serve as technical anchor across analytics, product, and ML teams, drive platform roadmaps, set standards, mentor engineers, and own end-to-end infrastructure decisions for scale and performance.

The Lead Data Engineer will design and develop technical solutions, collaborate with agile teams, and implement cloud-based data solutions, focusing on real-time data applications and big data technologies.

Lead Data Engineer responsible for designing, building, testing, and supporting scalable data pipelines and cloud-based solutions. Collaborate across Agile teams to optimize data models, ensure data quality and governance, mentor engineers, and apply distributed computing, streaming, and emerging GenAI tooling to deliver personalized marketing and messaging experiences.

Lead Data Engineer responsible for designing, building, and supporting scalable cloud data pipelines and platforms. Collaborate across Agile teams to implement distributed computing, data modeling, quality, governance, and real-time streaming solutions using Python, SQL, Snowflake/Databricks, Spark, Kafka, and cloud services. Mentor engineers, participate in code reviews, and drive technical innovation including GenAI tooling.

The Senior Data Engineer will design and execute data management strategies, build cloud solutions, develop data pipelines, and ensure data quality and integrity.

Lead architecture and delivery of scalable data infrastructure: design and optimize ETL/ELT pipelines, enterprise data models, and data quality frameworks. Define platform standards, mentor engineers, drive cross-functional initiatives, and partner with analytics, data science, and engineering stakeholders to ensure reliable, production-grade data assets.

The Senior Lead Data Engineer will design, develop, and support technical solutions, lead a team, and work with cloud-based services, focusing on data integration and transformation.

As a Senior Lead Data Engineer at Capital One, you'll lead a development team, utilizing various big data and cloud technologies to deliver impactful solutions. Responsibilities include collaborating with Agile teams, mentoring, and ensuring optimal code performance.

The Data Engineer will design and implement ETL frameworks, perform data analysis, troubleshoot data issues, and optimize data models to meet business needs.

Lead data engineer responsible for designing and building scalable databases, ETL pipelines, and data messaging platforms. Develop and optimize SQL/stored procedures, implement Spark/Snowflake/Databricks solutions, automate processes with Python and shell scripts, and collaborate with global business stakeholders using Agile practices to deliver accurate, accessible data for operational stores, archives, and analytics.

As the first Data Engineer, design and implement a scalable data platform, build data pipelines, and establish data modeling standards. Enable BI accessibility and document core metrics.