Top Remote Data & Analytics Jobs in Atlanta, GA

Designs, builds, and maintains Snowflake-based enterprise data warehouse solutions, including data architecture, ETL/ELT pipelines, security, deployment, data quality, modeling, and performance optimization. Partners with integration, analytics, governance, business intelligence, and architecture teams. Supports production operations, resolves ingestion and transformation issues, develops AWS-to-Snowflake scripts, documents implementations, and translates business requirements into scalable data solutions.

Leads market research and insights partnerships across operating groups, shaping research agendas and translating qualitative and quantitative findings into strategic recommendations. Manages and develops insights analysts in a matrixed environment, allocates resources across portfolios, oversees research quality and methodology, and presents actionable findings to executive stakeholders. Requires advanced research, statistical analysis, survey design, storytelling, stakeholder influence, and project management expertise.

Supports PMI’s research agenda through survey, qualitative, secondary, quantitative, business analysis, and foresight research. Analyzes AI, technology disruption, macroeconomic, industry, and future-of-work trends; translates complex findings into executive-ready insights, narratives, thought leadership, and strategic recommendations. The role requires rigorous methodology, independent initiative, cross-functional collaboration, strong communication, and the ability to assess technical developments and their business implications.

Designs, develops, and maintains scalable ETL/ELT pipelines and data platform capabilities for high-volume healthcare data. Responsibilities include complex SQL development, Airflow orchestration, dbt transformations, data quality frameworks, pipeline monitoring, troubleshooting, performance optimization, and documentation. The role collaborates with Data Operations, Product, Analytics, Data Science, and clinical teams to deliver reliable data for analytics, reporting, product features, and AI/ML initiatives.

Design, develop, and maintain scalable ETL/ELT data integration pipelines supporting analytics, reporting, and product capabilities. Build ingestion, transformation, validation, and curated data layers; optimize production workflows; document systems; and implement data quality monitoring and testing. Collaborate with implementation, engineering, analytics, and customer success teams to resolve data issues, support onboarding, and ensure reliable, accessible data.

Analyzes business performance data and delivers actionable insights for stakeholders and senior leaders. Develops dashboards, scorecards, KPI reports, and recurring brand reporting while ensuring data accuracy and reliability. Partners with sales, marketing, product, and technical teams to translate business needs into analytics solutions. Performs ad hoc analysis, identifies trends and risks, supports executive presentations, and communicates recommendations clearly.

Analyzes e-commerce performance, sales, conversion, traffic, profitability, digital shelf metrics, POS data, consumer behavior, and market trends. Builds executive dashboards and recurring reports, conducts forecasting and ad hoc analyses, and translates insights into recommendations for marketing, merchandising, product development, and channel strategy. Partners with cross-functional stakeholders to identify growth opportunities, improve processes, and support strategic business decisions.

Leads a multi-year migration from Amazon Redshift to Databricks on AWS, designs Medallion architecture and data models, develops SQL and Python ETL pipelines, and establishes data quality and governance standards. Manages 4–5 data engineers and Power BI developers while partnering with stakeholders to support trusted reporting and analytics. The role requires hands-on architecture and engineering, technical leadership, LLM-enabled workflow development, and clear communication across technical and non-technical teams.

Architect and lead enterprise data platforms, pipelines, and infrastructure using Spark, Databricks, and cloud technologies. Build scalable data models and dimensional schemas, establish governance and data quality frameworks, optimize performance and reliability, and implement monitoring. Partner with stakeholders to translate requirements into technical solutions, lead design reviews, mentor engineers, contribute to platform strategy, troubleshoot complex failures, and support hiring and team development.

Analyzes customer experience, survey, operational, CRM, ERP, support, and financial data to build unified customer views and actionable insights. Responsibilities include cohort analysis, segmentation, predictive modeling, revenue attribution, CX dashboards, reporting automation, and closed-loop action tracking. The role partners with IT, data teams, Finance, and business stakeholders to improve data quality and translate complex analyses into executive recommendations supporting retention, expansion, and customer experience improvements.

Analyze market and live data to set dynamic ticket prices using Uptick, build strategic pricing recommendations, communicate with clients about strategy and performance, and collaborate with BI and engineering to improve product performance.

Analyze healthcare operations data to identify bottlenecks, model advocate capacity and supply-demand, build scalable Hex dashboards, refine SQL and dbt data transformations, and translate complex findings into operational recommendations. The role partners with Operations, Engineering, Product, Marketing, and Finance to improve workflows, reporting, resource allocation, and business outcomes across the patient and advocate journey.

Leads LTK’s Data Engineering team, owning technical direction, architecture, pipelines, data products, governance, quality, reliability, and platform modernization. Manages and develops engineers, drives roadmaps and complex initiatives, partners with cross-functional stakeholders, and balances scalability, security, performance, cost, and business priorities. Establishes engineering standards, improves operational practices, manages risks and dependencies, and builds trusted, reusable data capabilities supporting analytics, reporting, products, and AI use cases.

Lead Workday reporting strategy for higher education: design Advanced, Matrix, Composite, and Dashboard reports; implement row-level security and role-based access; partner with HR/Finance/Payroll/Institutional Research; support regulatory and executive reporting; manage testing, validation, and user training while ensuring governance and data standards.