Top Hybrid Data & Analytics Jobs in Atlanta, GA

The Senior Enterprise Applications Engineer designs and maintains data architecture and pipelines, supports financial reporting, manages projects, and mentors junior members while utilizing business intelligence tools and emerging technologies.

The Data Analytics Engineer will develop data models, perform data wrangling, and create dashboards to drive insights for business decisions at Bose Corporation.

Lead analysis of marketing performance and campaign ROI, build and maintain dashboards, deliver actionable insights, and collaborate with cross-functional teams to inform targeting, segmentation, and predictive modeling efforts.

Support client engagements applying optimization, operations research, and AI-enabled analytics to logistics, transportation, warehousing, and distribution. Build models (LP/IP, network flow, heuristics, simulation), analyze messy data, design AI-enabled decision systems, produce client-ready deliverables, and collaborate with stakeholders to implement recommendations.

The Director leads a team in translating data into actionable insights for clients, managing high-performing teams, and applying business acumen in complex deal scenarios.

The GenAI Tuning Analyst improves Generative AI performance in contact centers through data analysis, prompt engineering, and collaboration with SMEs.

Lead North America GBO analytics team supporting merchant and acquiring partners. Deliver advisory engagements, build analytical tools, present insights, collaborate cross-functionally, coach staff, and drive OKRs using big data, visualization, and strategic recommendations.

Design and implement cloud-native Azure data architectures, data models, ELT processes, governance, and security. Collaborate with engineering, BI, and data science teams to optimize pipelines, ensure data quality, document designs, and support system stabilization for analytics and operational use cases.

The Principal Business Intelligence Analyst drives operational excellence by delivering data insights and supporting global Product Management and Engineering teams using data analytics, reporting, and KPI development.

Operate and support critical data pipelines and infrastructure, troubleshoot production data issues, perform root cause analysis, implement automation and monitoring, own incident management and on-call rotation, and create support documentation to ensure reliable, timely, and consumable data for stakeholders.