Data Engineer Jobs in Stamford, CT

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.

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.

The Data Engineer will execute data architecture projects, manage data ingestion processes, ensure data quality, and transition data to new systems while collaborating with investment teams.

Design, develop, and maintain Omni-based dashboards, visualizations, and reporting solutions. Manage data products throughout their lifecycle, ensure data quality and standardization, recommend scalable analytics approaches, and translate business needs into trusted data solutions. The role also provides training, ongoing support, enhancements, and subject-matter expertise in data visualization and reporting best practices.

Build scalable Python backend services, REST APIs, data ingestion pipelines, orchestration workflows, and data platforms. Develop reusable tooling, integrate diverse data sources, optimize databases and cloud infrastructure, and improve system reliability, observability, scalability, and cost efficiency. Collaborate with software, data, infrastructure, and business teams while contributing to architecture and production troubleshooting. The role also requires frontend development using Node.js, React, and React-Redux.

Responsible for data collection to support model training operations, building high-quality datasets, and managing the ingestion pipeline. Collaborate with AI team and scientists to enhance data quality and scalability.

Design and build end-to-end data pipelines and analytics in Microsoft Fabric, develop Power BI semantic models and dashboards, ensure data governance and quality, enable business stakeholders, and optimize performance and adoption across merchandising, supply chain, stores, and omnichannel.

Design and implement enterprise data security architectures focused on databases (SQL Server), Databricks, and object storage. Develop encryption, IAM, DLP, IRM/DRM, tokenization, and SecOps controls; secure data pipelines, perform vulnerability assessments, automate security tasks, and maintain policies and documentation while collaborating with development teams.

Design, build, and maintain scalable ingestion, normalization, validation, storage, and lifecycle management of large-scale market and alternative datasets. Develop Python- and SQL-based pipelines, monitoring, and tooling to ensure research-ready, high-quality data across multiple asset classes while collaborating with researchers and infrastructure teams.

The Data Operations Engineer will monitor and optimize trading processes, enhance integration and deployment pipelines, ensure quality control, and lead continuous improvement initiatives while documenting and reporting on production performance.