Top Senior Data & Analytics Jobs in Atlanta, GA

Owns business intelligence and data management for investment operations, developing Power BI dashboards, DAX and Power Query models, Snowflake reporting data, and secure data access. Leads strategic business initiatives, workflow improvements, technology enhancements, AI and LLM automation, stakeholder reporting, vendor coordination, requirements gathering, and project execution. Serves as the subject matter expert for data, reporting, client portals, metrics, and internal technology initiatives.

Designs, develops, and supports enterprise business intelligence solutions using Power BI and Qlik. Creates scalable dashboards, reports, and analytics to support business decisions; gathers stakeholder requirements; translates business needs into technical solutions; and maintains BI environments for performance, reliability, and data quality. The role may also apply AI-enabled analytics such as natural-language querying, anomaly detection, and automated reporting.

Leads customer segmentation, personalization, and customer master data strategy. Develops models, personalization roadmaps, data governance practices, and unified customer profiles to support targeted marketing and customer experience initiatives. Partners with CRM, marketing, analytics, technology, and operations teams; monitors KPIs; ensures data quality and privacy compliance; and manages a team of insights analysts and specialists.

Designs and leads cloud-native AWS data architecture for Medicaid and healthcare domains. Responsibilities include developing enterprise and domain data models, canonical models, metadata governance, data mappings, data quality and mastering processes, AWS prototypes, operational data stores, and implementation strategies. The role collaborates with governance committees, business owners, architects, developers, database administrators, and implementation teams while supporting compliance with PHI and PII protection requirements.

The Digital Analyst will build data products, own business datasets, troubleshoot tracking issues, analyze customer behavior, and deliver actionable insights. The role uses Adobe Customer Journey Analytics, Databricks, SQL, and Power BI to create reports, conduct ad hoc and deep-dive analyses, improve data collection, integrate external sources, and lead analytical projects. The analyst partners with technical and business teams to resolve instrumentation gaps and support data-driven strategy.

Performs independent quality assurance and validation across enterprise data platforms, warehouses, integrations, reporting solutions, and business processes. Responsibilities include data quality analysis, test strategy and automation, regression and release validation, incident investigation, root cause analysis, requirements traceability, governance, regulatory validation, and monitoring data quality metrics. The role partners with engineering, business, compliance, and operational teams while improving enterprise data integrity, reliability, and governance.

Leads the modernization of GreenSky’s Snowflake enterprise data platform, including data warehouse optimization, ETL/ELT modernization, governance, quality, observability, and self-service analytics. Defines multi-year data strategy and roadmaps, establishes engineering and deployment standards, enables AI/ML capabilities, and develops a team of data and test engineers while aligning platform investments with business outcomes.

Leads client experimentation and personalization programs across web, mobile, and media channels. Designs testing roadmaps, hypotheses, KPIs, audiences, and statistical parameters; oversees test execution, quality assurance, monitoring, and analysis. Translates results into executive recommendations, ROI projections, and strategic action plans. Advises clients on experimentation maturity, governance, prioritization, and best practices while training internal and client teams. Manages stakeholder relationships, concurrent roadmaps, and opportunities for account growth.

Leads the Underwriting Data Engineering team and oversees the design, development, and productionization of scalable data and machine learning pipelines. Responsibilities include feature engineering, data preparation, model deployment, data validation, governance, monitoring, API integration, analytic data products, roadmap development, stakeholder collaboration, and team coaching.

Develops market intelligence and analytical solutions using data mining, modeling, forecasting, scenario planning, and visualization. Partners with marketing, sales, supply chain, strategy, finance, and commercial stakeholders to manage data logistics, build data tools, validate outputs, identify market opportunities, and communicate actionable recommendations. Manages multiple projects, presents insights to executive audiences, and supports strategic decision-making.