Top Analytics Jobs in Atlanta, GA

Supports the development and maintenance of SQL and Python data pipelines, data models, semantic layers, dashboards, and reports. Performs data wrangling and preprocessing, collaborates with cross-functional teams to translate business needs into data solutions, and applies data governance, security, and quality practices. The role provides hands-on data analytics engineering experience supporting business analytics and AI initiatives.

Leads enterprise risk analytics strategy, teams, and oversight capabilities. Develops forward-looking risk indicators, dashboards, reporting, AI-enabled analytics, AML analytics, and continuous monitoring programs. Establishes standards for analytics governance, testing, documentation, validation, and quality assurance. Partners with senior leaders and cross-functional teams to translate analysis into strategic recommendations, improve risk management processes, and drive automation, standardization, and data infrastructure transformation.

Partners with business leaders to transform complex data into actionable insights. Leads analytics initiatives involving data analysis, KPI frameworks, experimentation, forecasting, performance measurement, dashboards, and visualization. Uses SQL, Python, Power BI, and cloud data platforms to support strategic decisions, improve customer experiences, and drive business performance. Collaborates with technology, data engineering, and governance teams while mentoring analysts and promoting data-driven practices.

Build and maintain production-grade data models while migrating workflows from Alteryx to dbt. Manage Dagster or Airflow pipelines in Redshift, create Tableau dashboards, and translate technical data into RevOps insights. Partner with Sales, Marketing, and Customer Experience leaders on KPI reporting, ABM, and customer health scoring. Explore AI, LLM, predictive analytics, and SageMaker machine learning applications including churn prediction and lead scoring.

Manage quantitative analytics consulting projects, including hypothesis development, data collection, modeling, analysis, research, and insight generation. Oversee analysts, collaborate with clients and partners, deliver high-quality project outcomes, manage demanding workloads, and coach team members. The role requires strong quantitative, communication, documentation, and presentation skills, proficiency with analytics software, and regular travel.

Leads advanced analytics initiatives using diverse data sources, predictive modeling, statistics, and trend analysis to solve business problems and guide strategic decisions. Builds and validates complex models, develops dashboards and reports, creates business cases, and advises stakeholders on data-driven recommendations. The role influences executive decisions, leads significant projects with autonomy, mentors staff, and drives improvements across multiple business lines.

The Senior Analytics Engineer builds and maintains data models, ETL pipelines, analytics products, business intelligence solutions, and visualizations. The role partners with stakeholders, Data Governance, Data Science, and Data Platform teams to define metrics, improve data quality, support AI and machine learning initiatives, and establish software engineering practices. Additional responsibilities include DataOps, workflow orchestration, technical documentation, business advising, and emergency response support. The position requires advanced SQL and Python skills, data engineering experience, and travel up to 10%.

Uses advanced healthcare analytics to identify member and client needs, evaluate programs, develop predictive models and segmentation criteria, measure clinical, utilization, and financial outcomes, and guide product innovation and business strategy. Partners with clinical and business leaders, conducts applied research, develops analytical methodologies, addresses data limitations, and communicates findings through reports, white papers, conferences, and publications.

Lead complex data analytics projects for private equity and corporate clients across the deal lifecycle. Translate data into actionable insights using visualization and modeling tools, improve data quality, build predictive models, collaborate with cross-functional teams, coach staff, interact with clients strategically, and validate outcomes to drive deal decisions and performance improvement.

Lead data-driven diligence and value-creation work for private equity and corporate clients. Manage teams and client accounts, perform complex analysis, develop predictive models and scenarios, build/maintain data pipelines and warehouses, improve data quality, and deliver visualizations and actionable recommendations using tools like Alteryx, Power BI, and Tableau.

Leads long-range workforce and resource planning for contact center operations. Owns demand forecasting, staffing, capacity, headcount, cross-skill, and scenario models across business lines and channels. Develops advanced predictive and prescriptive analytics, performance metrics, and decision-support tools using complex data sets. Advises executives on resource allocation, service levels, costs, and business performance while governing data quality and analytical processes. Leads capacity planning analysts and drives continuous improvement through automation, machine learning, and improved forecasting methodologies.

Leads reporting, analytics, and data infrastructure activities supporting U.S. business units. Supervises analysts, standardizes KPIs and reporting, ensures data quality, coordinates data engineering and governance with IT, supports M&A integrations, and oversees dashboards, financial reporting, dataflows, and analytics resources. Requires strong Power BI, Excel, SQL or R, automation, BI operations, and stakeholder-management skills.

Leads data and analytics engineering across cross-functional teams, translating business needs into technical solutions, managing data models and context layers, and ensuring data quality, governance, and accessibility. Establishes innovation environments, develops training and cross-skilling programs, mentors data professionals, supports self-service analytics and AI capabilities, and drives continuous improvement, technical reviews, and strategic data initiatives.

Analyzes digital product performance across web properties using Adobe Analytics, Google Analytics, tagging systems, statistical modeling, and data visualization. Develops measurement requirements, tracking specifications, dashboards, and actionable insights for product and marketing teams. Troubleshoots tags and data collection, supports experimentation and quality assurance, establishes analytics standards, and mentors analysts while communicating findings to stakeholders.

Uses SQL, Snowflake, Tableau, data modeling, and analytical techniques to identify trends, improve business processes, and deliver actionable insights. Builds data tools, maintains metadata, validates project outputs, creates dashboards and presentations, and communicates recommendations to stakeholders across marketing, sales, and supply chain. Manages multiple projects and may guide junior personnel.

Develop and maintain ETL/ELT pipelines across enterprise data lakes, warehouses, and BI platforms. Integrate, transform, validate, and monitor large datasets using Databricks, ODI, SQL, and Python. Support data quality, governance, metadata, lineage, semantic layers, dashboards, reporting, production troubleshooting, and operational maintenance. Collaborate with business and technical stakeholders to deliver scalable analytics solutions.

Own an analytics project for go-to-market teams by combining CRM, campaign, and account data with SQL and Python. Build reusable data models, define acquisition and pipeline metrics, investigate data quality issues, add validation checks, and create dashboards and analyses. Communicate findings, recommendations, assumptions, and limitations to stakeholders while documenting reproducible workflows.

Lead Workday reporting and analytics for HR: design, build, and maintain advanced Workday reports and integration data sources; manage reporting projects end-to-end; partner with HR COEs and HR Technology; mentor report writers; ensure data quality, governance, and audit readiness; and help extend analytics via Prism or Power BI and adopt AI-assisted capabilities.

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.

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.

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.

Designs, builds, tests, and supports enterprise data pipelines and Snowflake archival solutions for acquisitions, integrations, reporting, compliance, and analytics. Translates business and technical requirements into mappings, transformations, quality rules, and deployment plans. Collaborates with architecture, security, infrastructure, application, business, and vendor teams. Oversees validation, monitoring, documentation, cutover, go-live readiness, hypercare, and operational handoff while improving reusable, secure, cost-efficient data engineering practices.

Designs and implements governed enterprise data pipelines and Snowflake archival solutions supporting acquisitions, integrations, compliance, reporting, and analytics. Partners with architecture, security, application, infrastructure, business, and vendor teams to translate requirements into scalable pipelines, mappings, quality controls, monitoring, documentation, and deployment plans. Leads migration, cutover, validation, hypercare, and operational handoff activities while improving reusable engineering patterns, automation, performance, cost efficiency, and data observability.

Designs and supports claims data pipelines, integrations, ETL/ELT processes, reporting infrastructure, BI architecture, and automation solutions. Develops claims data models and analytics for segmentation, triage, assignment, and workflow optimization. Supports cloud platforms, AI-enabled predictive analytics, governance, validation, system integrations, testing, and deployment. Partners with Claims, IT, Finance, SIU, and Data teams to improve data accessibility, operational visibility, and reporting accuracy.

Design, develop, and maintain Power BI dashboards and reports; build data models, DAX measures, and Power Query ETL; perform statistical and geospatial analyses; validate and monitor data quality; collaborate with stakeholders to define KPIs; document solutions and present analytical insights to technical and non-technical audiences to support public health and program decision-making.