Top Senior Analysis Reporting Jobs in Atlanta, GA

Leads enterprise data architecture, SQL Server administration, data warehouse design, ETL/ELT pipelines, Azure data platforms, data governance, master data management, and business intelligence strategy. Partners with business and IT stakeholders to deliver scalable analytics solutions across financial, HR, CRM, operational, and practice management systems. Provides technical leadership, vendor coordination, architecture documentation, and mentorship.

Bridges procurement stakeholders, governance teams, business analysts, and engineers to define data contracts, map procurement data to OCDS, and build Databricks pipelines. Responsibilities include requirements gathering, source-to-target mapping, data modeling, validation, quality controls, lineage, governance, and production support. Develops Bronze, Silver, and Gold data layers using Spark, PySpark, Python, SQL, Delta Lake, and Databricks services while supporting Agile delivery, testing, deployment, and troubleshooting.

Build and run an enterprise data governance program: create policies, standards, and controls; establish data use and de-identification programs (HIPAA-compliant); define ownership and stewardship; measure and remediate data quality; maintain governance artifacts; align cross-functionally; report and drive adoption and training.

Provides operational visibility and business intelligence to Operations leadership through dashboards, automated reporting, KPI governance, and data analysis. Owns the Product Introduction Process and supports S&OP development, reporting, and continuous improvement. Consolidates ERP and business-platform data, prepares executive scorecards, identifies operational trends and risks, and coordinates cross-functional stakeholders across Sales, Planning, Purchasing, Logistics, Engineering, Manufacturing, Product Management, and Finance.

Leads enterprise Data and AI platform governance, operations, adoption, optimization, security, and compliance. Manages analytics strategy and team performance while overseeing data pipelines, predictive models, analytical databases, and workflows. Partners with technical and business stakeholders to translate needs into solutions, improve platform value, establish standards, and support responsible innovation. Responsibilities include recruiting, coaching, mentoring, cost optimization, vendor management, and communicating complex technical findings to diverse audiences.

The AVP, Data Engineer will design and build data ingestion, transformation, and replication pipelines using SQL, Python, dbt, and Dagster. Responsibilities include translating requirements into technical designs, developing data products, debugging production issues, supporting testing, and improving data engineering practices. The role also involves data modeling, mentoring junior engineers, conducting code reviews, and providing technical leadership while remaining hands-on. Experience with modern data platforms, workflow orchestration, cloud ecosystems, and insurance or financial services is preferred.

Leads enterprise database administration across SQL Server, Azure SQL, and Microsoft Fabric environments. Manages database security, performance, availability, disaster recovery, ETL platforms, scheduling, governance, audits, modernization, automation, and cloud adoption. Provides leadership to offshore DBAs, oversees vendors, drives upgrades and deployment standards, and partners with engineering, infrastructure, security, governance, and application teams to maintain reliable, compliant data platforms.

Analyze payment and banking transaction data across multiple sources to identify patterns, develop insights, and support data commercialization. The role includes exploratory analysis, data wrangling, quality checks, requirements development, reference data management, and client delivery. It requires collaboration with business, product, architecture, and engineering stakeholders, plus expertise in payments and banking data. The position is on-site Monday through Friday with approximately 10% travel.

Owns data infrastructure, datasets, dashboards, predictive models, and AI-enabled workflows for JLL’s national industrial real estate platform. The role supports investor and occupier business development through analytics, market research, supply-chain mapping, reporting, presentations, and executive insights. Responsibilities include coordinating cross-functional teams, improving data protocols, evaluating technology platforms, automating repetitive analysis, supporting pursuits, and communicating analytical priorities to leadership.

Develops and leads business intelligence solutions, data models, reporting, exploratory analyses, and data governance initiatives. Communicates insights to stakeholders, drives BI adoption, improves data literacy, ensures data quality, and partners across Product, Underwriting, Actuarial, Finance, IT, Claims, and Analytics. The role also includes peer code reviews, project roadmaps, strategic data initiatives, stakeholder advising, and onboarding and developing team members.