Top Senior Analysis Reporting Jobs in Atlanta, GA

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.

Configure and implement Informatica IDMC MDM solutions across customer, product, and supplier domains. Responsibilities include data modeling, match and merge logic, survivorship, golden records, hierarchies, data quality, governance, stewardship workflows, user access, testing, deployment, documentation, and production support. The role collaborates with business, governance, integration, and data engineering teams to deliver trusted enterprise master data.

Designs and administers scalable Tableau analytics platforms, optimizing dashboards, data sources, extracts, queries, and cloud infrastructure. Builds CI/CD pipelines and Python automation for Tableau, Snowflake, and Salesforce integrations. Establishes governance, security, monitoring, and performance standards while collaborating with Data Engineering and Analytics teams to deliver reliable enterprise reporting solutions.

Designs and maintains scalable enterprise analytics infrastructure centered on Tableau. Responsibilities include Tableau Cloud administration, architecture, dashboard performance optimization, security governance, CI/CD deployment, Python automation, and integration with Snowflake and Salesforce. The role partners with Data Engineering and Analytics teams to build reusable pipelines, reliable data models, monitoring capabilities, and high-performing analytics solutions.

Build and operate production data pipelines connecting marketing, CRM, licensing, payment, and operational systems with Databricks. Develop PySpark and SQL ETL/ELT workflows, dimensional models, APIs, data quality monitoring, identity resolution, and customer segmentation data flows. Support HubSpot enrichment, lifecycle marketing, campaign attribution, funnel reporting, and marketing ROI analytics while maintaining documentation, alerting, and incident response processes.

Administer enterprise Oracle, Microsoft SQL Server, and PostgreSQL databases in high-availability hybrid cloud environments. Responsibilities include database installation, configuration, maintenance, performance tuning, security hardening, encryption, backup and disaster recovery, and migration to Azure Government Cloud. The role supports contract management and financial tracking systems, applies DISA STIGs, manages clustering and partitioning, and ensures mission-critical data availability for government users.

Lead the redesign and implementation of a scalable Azure and Databricks lakehouse. Responsibilities include migrating Azure Data Factory pipelines, building Delta Lake architecture, developing SQL and Python transformations, establishing engineering standards, monitoring data quality, partnering with stakeholders, leading technical projects, mentoring engineers, and supporting future team growth.

Analyze complex datasets, optimize SQL queries, develop dashboards and visualizations, ensure reporting accuracy, and translate findings into actionable recommendations. The role supports strategic reporting and data-driven decisions while communicating insights to stakeholders. Experience with cloud data environments and AI-powered analytics tools is preferred.

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.