Top Senior Analysis Reporting Jobs in Atlanta, GA

Serve as a logical DBA supporting Land, Watershed, and Air branches. Troubleshoot and resolve database issues, develop ad-hoc queries and reports, ensure backups and recoverability, collaborate with third-party physical DBAs, design database functions, and work in cloud/SaaS environments. Provide systems integration, data modeling, and BI/reporting support.

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.

Independently validate and assure enterprise data quality across source systems, ETL/ELT pipelines, data warehouses and reporting. Lead incident investigations, root cause analysis, test strategy, automated validation, regression and non-functional testing, data governance metrics, regulatory validation, and stakeholder collaboration to drive continuous improvement in data quality and controls.

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

The Market & Business Intelligence Manager will lead analytics strategies, manage a team of business analysts, and provide insights to support firm strategy and decision-making.

The Program Director of Data & Analytics at Prologis will lead teams in transforming data through AI, overseeing budgets, resource allocation, and ensuring effective use of analytics tools while driving adoption and continuous improvement across data initiatives.

The Principal Data Engineer leads the development of scalable data solutions, collaborates on product roadmaps, influences organizational change, and coaches junior staff in a hybrid work environment.

Lead the design and migration of a data platform architecture. Manage data pipelines, mentor teams, and ensure platform reliability.

Define and manage internal data products using Big Data and advanced analytics to solve business problems. Own product lifecycle: roadmap, requirements, data asset identification, model feature definition, vendor selection, infrastructure coordination, testing, success measurement, and stakeholder/executive communication while ensuring compliance and risk controls.

Design, develop and unit-test Hadoop-based data solutions. Build ETL and MapReduce jobs using Hive, Pig, Sqoop, Java, R and shell scripts. Work with HDFS and HBase/NoSQL to support large datasets. Deliver detailed designs, code, unit tests and participate in quality and peer reviews.