Top Senior Data & Analytics Jobs in Atlanta, GA

Design and maintain scalable cloud data pipelines, ELT/ETL workflows, ingestion frameworks, and data models supporting cloud cost visibility and optimization. Use Python, SQL, dbt, Airflow, AWS services, and Snowflake to deliver reliable, auditable, cost-efficient data systems. Partner with Engineering and Finance stakeholders, optimize performance, ensure data quality, and support usage-based decision-making.

Analyze partner integration and operational data to identify trends, anomalies, bottlenecks, and root causes. Build data pipelines, models, dashboards, automation scripts, and operational tooling that improve efficiency, accuracy, monitoring, and scalability. Collaborate with engineering, product, and partner operations teams to translate operational challenges into technical solutions, reporting requirements, and process improvements.

Deliver analytics consulting projects involving process automation, data visualization, statistical analysis, and analytical tool development. Partner with stakeholders to identify business value, build minimum viable products and production applications, and train business users. Use tools such as Dataiku, Alteryx, Tableau, Power BI, Sigma, SQL, Python, cloud platforms, and modern databases while managing projects independently.

Leads the Digital Workplace analytics strategy, technology portfolio, KPI development, dashboards, data governance, predictive analytics, and actionable insights. The role drives digital platform adoption, connects usage data to business outcomes, ensures privacy and data integrity, communicates findings to senior stakeholders, and develops self-service analytics capabilities and data literacy across the organization.

Develops AI, analytics, SQL, Python, and Tableau solutions for Internal Audit across risk assessment, planning, testing, reporting, and continuous monitoring. Builds data extraction and reconciliation workflows, audit dashboards, repeatable testing scripts, and AI-assisted tooling. Assesses data lineage, controls, and risks across business systems, supports GRC administration, identifies automation opportunities, and trains audit staff on analytics and AI-enabled workflows.

Lead AI and automation performance reporting, develop KPIs and analytical frameworks, integrate data sources, evaluate analytical models, and deliver accurate, actionable insights. Partner with business and engineering stakeholders to improve monetization strategy, operational efficiency, and go-to-market decisions. Build Power BI dashboards, Microsoft Fabric semantic models, and cloud ETL/ELT solutions while ensuring privacy and data governance requirements are met.

Design, build, and maintain ETL/ELT pipelines and API integrations to ingest, cleanse, transform, and analyze infrastructure and cloud data. Produce analytics, dashboards, and executive reports; automate workflows and support near-real-time processing. Follow SDLC/DevOps practices (Git, CI/CD), ensure data governance, quality, lineage, and support incident, release, and compliance activities.

Design, build, and operate scalable batch and streaming data pipelines and analytics-ready data products on modern cloud platforms. Develop ETL/ELT processes, data models, monitoring, quality controls, metadata management, and governance workflows. Implement CI/CD and infrastructure-as-code practices, contribute to AI-enabled automation, and help ensure data assets are trusted, auditable, secure, and suitable for analytics and AI initiatives.

Own the end-to-end data architecture for multi-tenant enterprise SaaS and analytics products. Lead Azure SQL, Databricks, data lake, warehouse, BI, lifecycle management, ERP/SAP integration, observability, schema evolution, and data SLO initiatives. Manage DBA and database engineering standards, reliability, performance, HA/DR, and incident response while mentoring data engineers and partnering with product, projects, and BI teams.

Performs advanced risk analytics, reporting, data management, visualization, and modeling to identify portfolio trends, risks, control gaps, and business opportunities. Develops SQL-based datasets, dashboards, and executive reporting; investigates data quality and control issues; supports regulatory requirements; and partners with senior stakeholders on strategic initiatives. Uses automation and approved AI tools to improve analytical efficiency, process effectiveness, and risk-management outcomes.