Top Senior Data & Analytics Jobs in Atlanta, GA

Lead the strategy and governance for GTM analytics across pre-sales, post-sales, solutions engineering, forward-deployed engineering, and professional services. Establish trusted source-of-truth metrics, data models, semantic layers, self-service analytics, and AI-assisted querying. Partner with Data, Finance, Sales, and Services leaders to resolve metric definitions, improve data access, consolidate reporting, and guide cross-functional programs without direct authority.

Leads data engineering, data science, and AI initiatives, including Snowflake architecture, ETL pipelines, AWS data systems, data warehousing, analytics, and AI/ML solutions. Manages data governance, dashboards, experimentation, and web analytics integrations while building and mentoring multidisciplinary teams. Partners with Product, Editorial, Engineering, and business stakeholders to translate data needs into scalable solutions and drive business impact.

Supports client data and analytics engagements by designing validation approaches, building data integration and transformation solutions, analyzing data quality issues, testing pipelines with SQL, documenting findings, and recommending corrective actions. The role collaborates with clients, manages workstreams, mentors junior team members, and applies Agile methods while delivering risk and regulatory data solutions.

Designs, builds, and maintains secure data pipelines, ETL processes, data warehouses, and quality controls. Collects, validates, cleanses, and analyzes data; develops SQL queries, Tableau dashboards, and AWS-based solutions; investigates data integrity issues; documents standards; and partners with stakeholders to deliver technical solutions using Agile and DevOps practices.

Leads data ownership and governance for data products, defining metadata, quality, controls, integration, and risk mitigation. Partners with business, analytics, technology, and engineering teams to deliver curated datasets and production-ready solutions. Uses advanced SQL for validation and root-cause analysis, manages workstreams and staff, and supports analytics and machine learning use cases. Applies AI and LLM tooling to automate governance activities and maintains data integrity across regulated environments.

Build and maintain scalable batch, streaming, and real-time data pipelines, platforms, data lakes, warehouses, and lakehouses. Implement data quality, governance, security, observability, automation, and cloud modernization. Partner with product, engineering, analytics, data science, and business teams to deliver analytics, AI/ML, reporting, and customer insight solutions. Troubleshoot production issues, guide architecture, mentor engineers, and provide technical leadership across marketing data initiatives.

Designs, builds, and maintains complex data systems, including scalable data infrastructure, batch and streaming pipelines, data models, data products, and cloud-based architectures. Develops automated deployment pipelines, improves data systems, and supports data analysis and advanced analytics. Collaborates with cross-functional teams to gather requirements and ensure robust, governed, and accessible data solutions.

Leads enterprise data governance strategy, data quality standards, stewardship models, policies, metadata, lineage, classification, access controls, and lifecycle management. Partners with business and technical teams to resolve data quality issues, implement governance platforms, monitor KPIs, communicate risks, and maintain compliance with regulations such as HIPAA and GDPR.

Lead the design and implementation of enterprise-scale Knowledge Graphs and Semantic AI solutions, integrating graph intelligence and Generative AI. Manage cross-functional teams in data architecture and governance.

Leads enterprise information architecture, business intelligence, and data warehouse strategy and delivery. Oversees BI and data warehouse teams, establishes roadmaps and governance, mentors technical staff, manages project priorities, and ensures high-quality implementation. Designs enterprise data models, datamarts, metadata, ETL processes, reporting strategies, and integration artifacts. Partners with business and technology stakeholders to align data solutions with strategic goals, improve adoption, track value, and drive continuous improvement.