Top Analysis Reporting Jobs in Atlanta, GA

Lead a supply chain analytics team focused on process mining, network analysis, KPI development, and product-driven analytics. Partner with cross-functional stakeholders and DTS product teams to deliver data architecture, dashboards, automation, and strategic improvements that optimize end-to-end logistics operations.

Lead complex BI projects to define KPIs, build internal and client-facing Tableau/Power BI dashboards, enforce documentation and metric consistency, perform data analysis and profiling, create BI strategy and roadmaps, mentor junior analysts, and present insights to cross-functional and executive stakeholders.

Collects, scores, and enters client assessment data into the Clinical Database System; tracks clients and conducts follow-ups; performs basic statistical analyses, chart audits, and produces reports to support program evaluation and performance improvement.

Develop and support Informatica ETL solutions (70% development, 30% support). Build error-handling frameworks with Autosys/Control-M/Tidal, configure PowerCenter grid, work with IDQ, MDM, and Informatica Cloud. Perform performance tuning, Unix scripting, Teradata/SQL development, and data cleansing, standardization, and profiling.

Design, build, and maintain ETL jobs in IBM DataStage for an enterprise data warehouse. Analyze reporting requirements, implement complex transformations, monitor nightly loads, troubleshoot and refactor jobs, provide DataStage administration guidance, and maintain technical documentation while collaborating with other development teams.

Design and architect large-scale big data solutions using Hadoop, Spark and Python. Serve as technical lead engaging directly with clients and UI/UX architects, communicate designs clearly, and provide rapid problem-solving and guidance during implementation.

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.

As a Lead Data Engineer, you will architect data foundations for AI applications, lead a team, optimize data pipelines, and ensure data governance.

Lead and grow multidisciplinary teams to build scalable clinical data acquisition, engineering, governance, and product capabilities. Own data product strategy, SLAs, pipelines, and modernization using cloud-native tools and AI, while partnering with clinical, legal, and executive stakeholders to ensure compliant, discoverable, and trusted clinical data products.

Lead analytics strategy, semantic/reporting layer, and BI governance across Redshift/Athena and QuickSight/Tableau. Partner with platform teams on domain models, ensure data quality and documentation, mentor analysts, prioritize workstreams, communicate insights to executives, and optimize analytical workload cost and performance while enforcing data governance and access policies.