Data Engineer Jobs in Jersey City, NJ

As a Senior Associate in Data Engineering at PwC, you will design and implement data architecture strategies, analyze complex issues, mentor junior members, and build client relationships while ensuring adherence to project standards.

As a Senior Manager in Data Engineering, you will lead teams to design data architectures, develop data solutions, manage client engagements, and ensure compliance with data governance policies.

Lead data engineering projects, develop and implement data pipelines and architecture strategies, manage data quality, and mentor team members at PwC.

Design and build data infrastructure, pipelines, and integration solutions using cloud and big-data tools. Develop data lakes/warehouses, ensure data quality and security, apply data modeling and DAGs, use Databricks, Airflow, and Hadoop, and collaborate with clients to deliver actionable insights.

Design, implement, and deploy scalable AI/ML systems. Perform data wrangling, preprocessing, and advanced algorithm development. Collaborate with cross-functional teams to integrate AI solutions, analyze complex datasets for business insights, and support client engagements while continuously improving technical skills.

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.

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 a Data Engineer, you will design and implement scalable data architectures, oversee integration and governance while collaborating on Master Data Management frameworks, to optimize data performance and drive innovation across the organization.

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.

Design, build, and operate petabyte-scale data pipelines for AI training and evaluation. Handle ingestion across modalities, data cleaning, deduplication, versioning, lineage, high-throughput loading for accelerator training, labeling/active-learning workflows, privacy/redaction, storage architecture, observability, and cost/performance optimization while collaborating with ML researchers and documenting systems.

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

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.

Lead design and delivery of enterprise-grade CRM and analytics data integration solutions. Build and operate batch and near-real-time ETL/ELT pipelines, Python automation, and SQL/NoSQL data models. Ensure data quality, security, observability, and operational ownership while partnering with architecture, application, and business teams.

Lead development of AI and ML solutions for healthcare systems, overseeing teams, driving use case development, and ensuring operational excellence while managing global delivery operations.

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

Lead the design and optimization of batch and streaming data pipelines, ensuring high-quality data delivery for AI and analytics, while mentoring and promoting engineering best practices.

Analyze transaction data to detect fraud, develop controls and rule-engine logic, automate data workflows, build dashboards and reports, partner with data science on fraud models, monitor model performance, and advise stakeholders on fraud strategy and risk.

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

The Senior Data Engineer Lead will design, build, and oversee data architecture, mentor engineers, and drive data strategy and culture at Citi.

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

Build and maintain high-performance, fault-tolerant distributed backend services and data pipelines for large genomic and health datasets. Design storage, indexing, and async event workflows; optimize latency, throughput, and reliability. Partner with bioinformatics and product teams to validate scientific accuracy and guard AI-driven responses.

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.