Top Senior Level Data & Analytics Jobs

The Senior Technical Implementation Analyst at McKesson will deliver technical solutions for customer implementations and manage project requests. Responsibilities include configuring software/hardware, documenting processes, leading testing phases, improving internal processes, and interacting with stakeholders to resolve issues and ensure project success.

As the Director of Data and Analytics at Nutrabolt, you will lead the consumer insights team, develop marketing analytics capabilities, and drive optimization of marketing investments through data-driven insights, collaboration, and effective decision-making.

The Senior Director of Engineering and Data Science at Fluence leads software engineering and data ops teams, focusing on developing AI-based solutions and aligning initiatives with business goals. The role involves shaping architectural decisions, optimizing performance, and fostering a culture of innovation. Collaboration with executives and mentoring team members are also key responsibilities.

As a Data Platform Engineer, you will design and build data architecture, collaborate with business functions to develop data products, and optimize data pipelines using modern tools and frameworks. You'll also lead data engineering initiatives to support analytics and reporting needs.

As a Senior Manager Data Analytics, you will lead a team focused on marketing analytics, providing insights to improve marketing effectiveness, and developing dashboards and test plans. You will identify trends and opportunities through proactive data analysis and communicate findings to influence stakeholders for better decision-making.

As a Senior Data Engineer, you will design, develop, and maintain data platforms to support organizational data needs, build scalable data ingestion pipelines, lead data governance efforts, and collaborate with Data Scientists and Product Managers to implement data models and ETL processes, predominantly using AWS technologies.

The Senior Data Engineer will collaborate with cross-functional teams to design and implement data ingestion, modeling, and transformation processes. Responsibilities include building ETL pipelines, creating data marts, monitoring the data platform, and deploying machine learning models to enhance business intelligence.