Top Analysis Reporting Jobs in Atlanta, GA

Leads data ownership and governance for data products, defining metadata, quality, controls, integration, and risk mitigation. Partners with business, analytics, technology, and engineering teams to deliver curated datasets and production-ready solutions. Uses advanced SQL for validation and root-cause analysis, manages workstreams and staff, and supports analytics and machine learning use cases. Applies AI and LLM tooling to automate governance activities and maintains data integrity across regulated environments.

Lead and grow an enterprise data engineering team while owning the Snowflake and Airflow platform roadmap. Build reliable, governed data products and modernize pipelines using AI-assisted and agentic workflows. Establish standards for quality, observability, lineage, cost efficiency, incident response, and documentation while partnering with Analytics, Data Science, Product, and business stakeholders.

Build and maintain scalable batch, streaming, and real-time data pipelines, platforms, data lakes, warehouses, and lakehouses. Implement data quality, governance, security, observability, automation, and cloud modernization. Partner with product, engineering, analytics, data science, and business teams to deliver analytics, AI/ML, reporting, and customer insight solutions. Troubleshoot production issues, guide architecture, mentor engineers, and provide technical leadership across marketing data initiatives.

Designs, builds, optimizes, and supports scalable AWS-based data infrastructure, pipelines, data models, and ETL/ELT processes using Python, SQL, PySpark, Databricks, and Spark. The role supports analytics, reporting, and business intelligence through production monitoring, troubleshooting, testing, CI/CD, documentation, and cross-functional collaboration with BI, Product, Engineering, Data, and client-facing teams.

Lead the design and implementation of enterprise-scale Knowledge Graphs and Semantic AI solutions, integrating graph intelligence and Generative AI. Manage cross-functional teams in data architecture and governance.

The QC Manager ensures the integrity of the Neighborhood Captains program, monitoring data quality, conducting voter follow-ups, managing plants, and supporting Organizers with actionable insights.

Build and operate scalable data engineering services supporting Workday’s machine learning and agentic initiatives. Responsibilities include data ingestion, governance, discoverability, derivation, and serving using Python, Spark, AWS, Kafka, Terraform, Kubernetes, and Iceberg. The role involves distributed systems development, production deployment, monitoring, testing, performance optimization, security, on-call support, and collaboration with engineering teams.

Conducts mixed-methods workplace research to evaluate office layouts, furniture, programs, and technology. Designs and executes qualitative and quantitative studies, performs on-site fieldwork, analyzes spatial telemetry and employee sentiment, and translates findings into actionable recommendations. Partners with workplace innovation and space insights teams throughout pilot lifecycles, while using AI tools and automated workflows to accelerate research synthesis and reporting.

Leads business intelligence teams supporting Microsoft’s global datacenter supply chain. Responsibilities include data analysis, reporting, governance, executive storytelling, analytics automation, evaluation, and cross-functional collaboration. The role develops scalable self-service insights, improves data quality, partners with Engineering and Data Science teams, coaches employees, and presents actionable recommendations to senior stakeholders.

Designs and maintains Azure data pipelines, analytics architectures, Power BI dashboards, automated workflows, data governance controls, APIs, and conversational solutions. Partners with business and technical stakeholders to transform enterprise operational data into actionable insights. Troubleshoots Power Platform applications, supports end users, and ensures data security, compliance, reliability, and deployment quality across cloud analytics solutions.