Top Senior Data Engineer Jobs in NYC, NY

Lead the evolution of data platform by designing scalable pipelines, improving data processes, mentoring teams, and modernizing data architecture.

Manage delivery of complex data pipelines in a hands-on role, leading a team of data engineers to develop scalable data solutions and improve analytics capabilities.

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 Data Engineer will design and optimize ETL pipelines, integrate data, ensure data integrity, tune SQL queries, troubleshoot issues, and collaborate with teams to create data solutions.

As a Sr Data Engineer, you'll conduct feasibility analyses, develop applications, monitor processes, consult with users, and ensure compliance while serving as a mentor to junior analysts.

The Senior Consultant, Data Engineer will design modern data platforms, build workflows, and translate business needs into technical solutions across various industries.

The Principal Data Engineer will lead complex data projects, design robust data pipelines, and drive architectural strategy for a scalable data ecosystem, while mentoring other engineers and ensuring the quality and usability of data solutions.

Design, build, and operate scalable Spark-based ETL/ELT pipelines and data platforms on AWS. Manage end-to-end data lifecycle, ensure data quality and observability, optimize performance and costs, enforce CI/CD and IaC best practices, and collaborate with stakeholders to deliver production-grade analytics solutions.

This role involves developing data pipelines, ensuring data performance, automating processes, and collaborating within Agile teams to meet complex data requirements.

The Senior Staff Data Engineer will design scalable data systems, lead technical direction, optimize data platforms, and ensure data quality and performance for Observability & Insights.

Build user-facing data products by transforming internal data into actionable metrics. Collaborate with platform teams and data scientists to prototype, validate, and prioritize data sources. Write requirements and proposals, engage in user research, and deliver performant Python/SQL-based data features using Databricks and Postgres.

In this role, you'll build and scale high-throughput data pipelines, ensure data quality, and leverage AI for improved data operations. You'll also lead initiatives in a fast-paced environment focused on real estate data engineering.

Design, develop, integrate, test, and optimize scalable data integration solutions and pipelines for the OneGL finance environment. Support production users and month-end close processes, troubleshoot issues, develop test scripts, and document architectures. Collaborate with technical and business stakeholders, perform gap analysis, and support implementation and post-implementation activities.

Design and build foundational dimensional data models, enterprise metrics, and curated data products on a modern lakehouse. Partner with business domains to translate processes into scalable, high-quality datasets, optimize analytical workloads, and operate distributed processing systems to support analytics, BI, and AI.

Design, build, and maintain scalable Spark-based ETL pipelines and computed tables in a central data lake. Integrate structured and unstructured IoT, sensor, and external data for analytics, model training, and dashboards. Collaborate with Data Science, Analytics, and ML teams to ensure reliable, high-quality customer-facing datasets.

The Data Engineer will design and maintain data pipelines on Azure, manage ClickHouse for analytics, and ensure healthcare compliance while supporting ML integration.

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.

Design, build, and operate large-scale data platforms and Spark/PySpark pipelines. Enable data integration, modeling, quality, and observability. Build MCP servers and AI-augmented tooling, mentor engineers, and lead cross-functional projects to deliver reliable data products.

Own and architect large-scale data pipelines, orchestration, and integrations. Drive IaC strategy (Terraform), third-party API and AI/LLM tool integrations, build export pipelines and internal tooling, mentor engineers, and align cross-team technical strategy for reliable, scalable data infrastructure.

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 Principal Data Engineer will lead the design of data frameworks, mentor teams, implement MDM solutions, and ensure data quality across environments.

Lead design, build, and maintain scalable data pipelines and infrastructure using Azure Databricks, ADF, and SQL Server. Develop OLTP and dimensional models, integrate Salesforce and SaaS sources, implement batch and real-time processing, enforce data governance and CI/CD, troubleshoot performance, mentor team members, and drive improvements to reduce technical debt and improve cost and performance.

As a Senior Data Engineer, you will design and maintain scalable data models, build production data pipelines, and support analytics across various business functions.

Design, build, and maintain scalable data ingestion and ETL pipelines across a growing data lake. Define and enforce data quality standards, SLOs, and validation frameworks. Optimize pipelines for performance and cost, expand monitoring and alerting, and enable stakeholders to self-serve on data infrastructure.

Responsible for designing, developing, and maintaining databases and ETL systems to support business applications and business intelligence. Collaborates with stakeholders to align business requirements and leads the design of automated solutions for operational efficiency.