Data Engineer Jobs in Jersey City, NJ

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.

Lead design, development, and operation of large-scale Spark-based data pipelines and lakehouse solutions. Write and review Python/PySpark and Spark SQL production code, optimize Spark workloads on EMR/Databricks, manage Apache Iceberg table operations, drive AI-assisted engineering adoption, automate reliability and CI/CD practices, and lead technical evaluations and communities of practice.

Design, build, test, and maintain secure, scalable data collection, storage, access, and analytics solutions. Develop and maintain ETL pipelines and data architectures, update logical/physical data models, review data controls, perform statistical data analysis, customize tooling to generate products, and work with SQL and NoSQL databases.

Lead and deliver secure, high-quality software solutions for financial planning and analysis. Design, develop, review, and troubleshoot production code; drive adoption of enterprise AI-assisted engineering practices; leverage AWS and big-data technologies like Spark; evaluate vendors; automate remediation to improve operational stability.

Partner with sales teams to design and present data security solutions, gather technical requirements, lead hands-on evaluations and custom configurations, design evaluation test plans, and guide prospects to successful outcomes.

Lead design, build, deploy, and maintain production-grade ML/data platforms and end-to-end model pipelines. Engineer large-scale data ingestion, transformation, storage (data lakes/warehouses), monitoring, CI/CD, and production reliability. Resolve production incidents quickly, add features, and drive adoption of enterprise AI-assisted engineering practices while ensuring responsible AI, security, and validation standards across the team.

Lead Data Engineer responsible for building, optimizing, and operating secure, scalable data pipelines and platforms. Develop and run batch and streaming pipelines, workflow orchestration (Airflow), SQL-based transformations, and production-grade Python/PySpark code. Collaborate with analysts and data scientists, own system reliability and security, mentor junior engineers, and apply enterprise-authorized AI tools with strong validation and data sensitivity practices.

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 Market Data Platform Engineer will design and implement a low-latency market data distribution platform, focusing on performance optimization, architectural decisions, and collaboration with global teams, particularly in Equities trading.

The Data Engineer will analyze, develop, implement, test, and support data warehouse projects. Responsibilities include project support, data validation, and enhancing data management processes, all while collaborating with team members and improving performance.

Data Engineer will develop and support data warehouse projects, analyze data integrations, work with ETL tools, and improve processes while collaborating with team members.

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.

The Data Engineer designs and builds data pipelines for analytics, ensuring data quality, governance, and integration across systems, while collaborating with teams for effective delivery.

Lead Software Engineer responsible for designing, building, and maintaining scalable data pipelines and platform components (cataloging, quality, lineage, governance). Implements data modeling, partners with stakeholders to deliver production-grade code, automates operations, evaluates vendors, and leads Agentic Autonomous Lakehouse and engineering communities to drive platform innovation and operational stability.

The Data Engineer will develop and optimize data pipelines for LLMs, ensuring high-quality healthcare datasets while collaborating with data scientists on model requirements.

Role focuses on ensuring data center security and resiliency, implementing controls and controls compliance, and protecting export-controlled information. The posting emphasizes eligibility to access export-controlled data and does not list specific technical duties or tools.

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 design and delivery of complex data solutions including data integration, cleaning, transformation, lineage, and migration. Build and document data pipelines, manage ADS and regulatory data lineage, lead testing and cutover for database migrations, create automation and reconciliation scripts, troubleshoot with architects and security teams, and mentor other data engineers.

The Business Intelligence Engineer develops and maintains Power BI reports and dashboards, supports data validation, and collaborates with team members to ensure reporting accuracy and effectiveness. The role includes working with SQL for data retrieval and assisting in report enhancements.

Lead development of AI‑first analytics and data products, modernize the data mesh, build autonomous human‑in‑the‑loop agents for schema drift and governance, design scalable batch and real‑time pipelines, enforce lineage/DQ/governance, and provide technical leadership across analytics, platform, risk, and domain teams.

Lead design, development, and production support of secure, cloud-native data and analytics systems. Drive adoption of AI-assisted engineering practices, improve automation and resiliency, evaluate vendor solutions, and mentor teams on secure, scalable software delivery.

Lead design and implement scalable hybrid cloud solutions for transactional, analytics, and RAD workloads. Write and review code, drive AI-assisted engineering adoption, apply SDLC tools, collaborate with leads and stakeholders, conduct code reviews, present technical updates, prioritize work, and mentor team members.

Lead design, build, and operate scalable data platform components and pipelines (batch and real-time) using Spark, Flink, Kafka, Airflow and Databricks. Implement data modeling, governance, cataloging, observability, and production-grade code; partner with stakeholders and lead technical evaluations and communities of practice.