Top Analysis Reporting Jobs in Atlanta, GA

Leads the enterprise ontology for insurance coverage, exposure, underwriting, claims, and loss data. Defines business concepts, schemas, classifications, mappings, lineage, governance standards, and data quality rules. Integrates internal, carrier, IVANS, catastrophe, geospatial, and other third-party data. Partners with underwriting, claims, analytics, technology, governance, product, and regulatory teams to enable trusted reporting, AI, predictive modeling, and operational workflows while maintaining alignment with ACORD and industry requirements.

Leads business intelligence and decision analytics strategy, overseeing data systems, reporting, optimization models, data quality, budgets, and cross-functional teams. Uses supply chain, customer, product, transactional, and financial data to identify operational and distribution improvements that increase profitability. Partners with senior leaders to implement advanced analytics capabilities and promote data-driven decision-making across the organization.

Designs and executes large-scale data migrations and conversions into Fiserv products. Builds custom database solutions and reusable ETL tooling, ensures data integrity, supports integrations, and leads go-live troubleshooting and incident response. Collaborates with clients and product teams on requirements and technical designs, evaluates database technology components, and may assist with hiring and staffing allocation management.

Manages Microsoft Azure, Fabric, and SQL Server data platforms across cloud and on-premises environments. Responsibilities include platform support, monitoring, performance tuning, CI/CD and orchestration management, database backup and disaster recovery, deployments, automation, security controls, governance, data lineage, compliance, incident response, and root cause analysis. The role participates in on-call support, platform upgrades, auditing, documentation, and testing of new Azure and Fabric capabilities.

Analyzes customer account data, SLA performance, service metrics, and escalations across delivery hubs. Builds Excel dashboards, pivot tables, scorecards, trackers, and leadership reporting materials. Partners with Operations to validate data, identify root causes, detect risk patterns, and support issue resolution. Maintains data integrity and governance while contributing to reporting standardization and process improvements.

Develop and maintain data models, semantic layers, dashboards, and Python- and SQL-based reports for claims analytics. Analyze operational performance, investigate root causes, and provide actionable recommendations to leadership. Collaborate with engineering, operations, and other stakeholders to translate source systems into standardized data models and deliver effective analytical solutions. Communicate findings through clear writing and presentations while helping shape a growing data team.

Operationalize and manage enterprise governance across AI, automation, data, analytics, and product investments. Own policies, standards, exceptions, committee operations, maturity tracking, stakeholder requirements, business cases, data catalog and lineage tools, risk scoring, security controls, training, and leadership reporting. The role requires business analysis, data governance, AI risk assessment, regulatory awareness, requirements translation, Agile delivery, and collaboration with technical and non-technical stakeholders.

Operationalize and manage enterprise governance across AI, automation, data and analytics, and product investments. Own governance policies, exceptions, committee operations, maturity tracking, stakeholder requirements, risk scoring, data catalog and lineage processes, security and privacy controls, reporting, and user enablement. The role requires business analysis, data governance, AI risk assessment, regulatory awareness, Agile delivery, and collaboration with technical and non-technical stakeholders.

Lead SAP data workstream for ECC to S/4HANA Brownfield migrations: define strategy and roadmap; oversee extraction, profiling, cleansing, transformation, reconciliation, and validation of master and transactional data; run mock conversions, cutover planning, and post-go-live reconciliation; establish data quality, governance, stewardship, controls, and training; manage risks, defects, and stakeholder reporting.

Design, build, and maintain Databricks-based data platform and ETL/ELT pipelines. Collaborate with stakeholders, implement data quality checks and testing, monitor pipeline performance, document architecture, and coordinate cross-functional teams.