Data Engineer Jobs in Jersey City, NJ

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.

Designs, deploys, validates, and operationalizes AI/ML solutions for infrastructure reliability, forecasting, observability, automation, and enterprise decision-making. Builds models, NLP capabilities, data pipelines, APIs, dashboards, and MLOps workflows across hybrid cloud and on-premises environments. Manages the model lifecycle, including governance, validation, monitoring, remediation, and production support. Partners with engineering, operations, risk, cybersecurity, architecture, data science, and product teams while communicating technical outcomes and risks to technical and executive stakeholders.

Senior individual-contributor responsible for shaping enterprise data product strategy, translating business requirements into governed data assets, and driving modernization of cloud-based data platforms. Collaborates with senior stakeholders to enable analytics, AI-assisted data consumption, data governance, metadata/lineage, and self-service capabilities while ensuring scalable architecture, data quality, and regulatory readiness across data product lifecycles.

The Databricks Data Engineer will design and implement ETL pipelines, manage data ingestion processes, and collaborate with business teams to create analytics solutions.

Design, build, and maintain high-volume security data models and pipelines in Snowflake. Ingest, normalize, enrich, and correlate telemetry for detection engineering and threat hunting. Partner with security teams, enforce data standards, drive data governance, performance optimization, vendor management, and mentor engineering teams. Conduct POCs and produce integration and process documentation.

Design and maintain canonical data models and pipelines to inventory cryptographic assets and CBOM outputs. Build Power BI dashboards and semantic models, write complex SQL for analytics, ensure data quality and governance, and partner with security, IAM, PKI, and risk teams to support PQC readiness and enterprise risk reporting.

Design, develop, test, and deploy high-performance Spark/Scala data processing applications and ETL pipelines using the Cloudera Hadoop ecosystem. Optimize Spark and platform performance, ensure data integrity and security, collaborate with data scientists and analysts, troubleshoot issues, and implement version control and CI/CD for Spark applications.

Design, develop, test, optimize, and deploy large-scale Spark/Scala data processing and ETL pipelines on Cloudera Hadoop. Collaborate with data scientists and analysts, ensure data integrity and security, troubleshoot performance, and implement version control and CI/CD for Spark applications.

Design, implement, and maintain Java-based applications to automate financial data reconciliation across relational and NoSQL sources. Build deterministic and heuristic matching algorithms, integrate with rules engines (Drools), handle errors and exceptions, collaborate with analysts and architects to resolve data gaps, and support data governance and quality initiatives.

Design, implement, and maintain Java-based applications to automate complex data reconciliation across relational and NoSQL sources. Build matching algorithms, integrate with rules engines (Drools), handle data streams, perform gap analysis, and collaborate with analysts and architects to ensure data quality.

Lead design, development, and delivery of enterprise data warehouse and analytics solutions using Snowflake and modern data engineering tools. Build and optimize ETL/ELT pipelines, ensure data quality and performance, mentor engineers, support production platforms, troubleshoot incidents, and partner with stakeholders to translate requirements into scalable analytics solutions.

Lead design, build, and maintain scalable batch and real-time data pipelines, ETL/ELT workflows, data warehouses/lakehouses, and streaming solutions. Optimize performance, ensure data quality, security, observability, and CI/CD for production systems while mentoring engineers and collaborating with stakeholders for analytics and ML needs.

Lead architecture and hands-on development of cloud-native AI web applications. Design end-to-end solutions integrating LLMs, vector search/RAG, real-time data, and scalable backend services. Implement model serving, RAG pipelines, AI agents, and ensure quality via testing and CI/CD while leading cross-functional engineering teams and translating business requirements into production-ready systems.

The role involves developing Java-based applications, collaborating with business users, managing testing strategies, and supporting compliance in a regulatory context.

The role involves leading the design and delivery of multi-agent systems for underwriting and claims automation, ensuring production readiness and business alignment.

Design, build, and maintain scalable data pipelines and infrastructure on AWS, collaborating with data scientists and AI teams to support analytics and ML initiatives.

Design, build, and maintain end-to-end batch and streaming data pipelines on GCP. Migrate legacy warehouses to BigQuery/Bigtable/ClickHouse, orchestrate workflows in Airflow, ensure data quality and observability, and partner with ML engineers on feature pipelines, drift monitoring, and retraining.

Lead ETL and data architecture for AML, trade/sales surveillance, and compliance data repositories. Design and develop complex Informatica PowerCenter 9.1 mappings, enforce ETL architecture standards, tune performance, automate and maintain ETL utilities, collaborate with BAs and DBAs, provide production support, and mentor junior ETL developers.