Top Senior Data & Analytics Jobs in Hartford, CT

As a Data Engineer, you will design and maintain data pipelines, support DoD systems, and ensure data quality and compliance.

The Senior Data Scientist will analyze and optimize marketing funnels, build statistical models, conduct experiments, collaborate with teams, and mentor junior members.

The Senior BI Analytics Engineer will design and deliver data models for analytics, ensuring data quality, and collaborating across teams to enhance AI-driven reporting and querying capabilities.

Design, develop, and maintain enterprise Power BI dashboards and reports. Integrate data from SQL Server, Azure, Excel and other sources, perform data modeling and DAX calculations, validate data, and document data models and reporting logic while partnering with business stakeholders.

As Senior Manager of IT Commercial Data Management, you will lead data initiatives, manage product ownership, and develop data governance strategies in collaboration with stakeholders, ensuring high data quality and analytics capabilities.

The IBM TM1 Developer will manage the SDLC for Finance applications, focusing on TM1 and migrating from Essbase, while collaborating with global teams.

Serve as a client-facing consultant translating business needs into technical specifications, delivering Liquid Data platform solutions, developing reports/dashboards, supporting implementations, and driving technology adoption while collaborating with internal teams and leveraging cloud, API, and BI integrations.

As a Senior Data Engineer, you'll design and maintain scalable data pipelines, optimize workflows with dbt and Snowflake, and mentor teams across functions to enhance data reliability and performance.

The Data and Reporting Architect will lead the design of data architectures and reporting systems, addressing complex data challenges and ensuring compliance with regulatory standards. Responsibilities include mentoring engineers, defining data quality frameworks, and collaborating with various teams to implement scalable solutions.

Partner with customers and sales to design and present scalable Databricks Lakehouse architectures, build reference architectures and demos, consult on big data, ETL, and ML projects, validate integrations, and drive technical wins and adoption across accounts.