Top Senior Business Intelligence Jobs in Atlanta, GA

Leads Sales Business Intelligence strategy and AI transformation as a senior individual contributor. Develops enterprise Power BI dashboards, data models, SQL transformations, metrics frameworks, AI agents, and automated analytical workflows. Partners with sales leadership, IT, engineering, security, and governance teams to deliver trusted insights, improve adoption, reduce manual reporting, and influence revenue decisions. Mentors analysts and drives AI-enabled ways of working without direct people-management responsibility.

Designs and develops scalable data platforms and architectures using Azure or AWS. Translates business objectives into technical solutions, supports data warehousing, business intelligence, master and reference data management, and develops data-as-a-service capabilities. Leads client initiatives, establishes architectural governance, creates system diagrams, analyzes business processes, advises on emerging technologies, and mentors junior data professionals. The role involves significant client interaction and 30–50% travel, with remote work from a home office when not traveling.

Leads enterprise business data strategy, governance, analytics, business intelligence, AI enablement, and data modernization. Partners with executives and cross-functional leaders to establish data ownership, improve quality, develop analytics and KPI frameworks, prioritize AI use cases, and measure transformation value. Builds data-focused organizational capabilities, drives adoption and data literacy, develops investment cases, and guides enterprise initiatives that improve forecasting, planning, operational decisions, and business outcomes.

Leads enterprise business data strategy, governance, analytics, business intelligence, AI enablement, and modernization initiatives. Establishes data ownership models, roadmaps, KPIs, and governance frameworks while partnering with executives and business functions. Builds data and analytics capabilities, develops investment cases, drives transformation value realization, promotes data literacy, and leads cross-functional change to improve decision-making and business outcomes.

Build and maintain branch network performance reporting, dashboards, semantic models, and analytical datasets using SQL and Alteryx. Translate banker, branch, market, and enterprise data into actionable insights for senior leaders. Lead analytical projects, manage timelines, communicate executive-ready findings, improve reporting processes, and mentor junior analysts. Partner with Distribution and Consumer Bank leadership in a hybrid, primarily onsite environment.

Senior Business Intelligence Analyst responsible for campaign KPI development, forecasting, data integration, dashboard creation, performance analysis, and optimization recommendations. The role manages and troubleshoots the agency’s data stack, including Improvado, Snowflake, and Tableau, while partnering with media, advertising, and communications teams. Requires strong SQL, Python, R, spreadsheet, analytics, database, and data-cleaning expertise. This is a remote, four-month W2 contract requiring PST availability.

Senior individual contributor leading Sales BI strategy and AI transformation. Responsibilities include developing enterprise Power BI dashboards and data models, defining sales metrics, delivering production AI agents and automated analytical workflows, shaping Snowflake and AI analytics infrastructure, leading cross-functional initiatives, mentoring analysts, and influencing sales executives through data-driven recommendations. The role requires measurable adoption and business impact from AI-enabled analytics, without direct people-management responsibility.

Leads business intelligence and analytics for Verizon’s Business Markets Group. Designs measurement programs, develops advanced geospatial and financial models, evaluates sales and operational approaches, standardizes metrics, and converts complex data into strategic insights. Partners with business, technology, marketing sciences, and operational analytics teams while leading cross-functional data initiatives.

Own the architecture and standards for a trustworthy BI analytics platform. Design data models, ingestion and transformation patterns, lineage, PII controls, reliability SLAs, observability, schema governance, and cost management. Partner with engineers, analysts, business leaders, Security, Legal, and Compliance; enforce testing, CI/CD, infrastructure as code, and data quality practices. Mentor data professionals and document architectural decisions.

Develops business intelligence solutions using data from diverse sources to deliver insights, visualizations, process automations, and decision support. The role analyzes complex business opportunities, integrates and refines organizational data, presents findings to senior leaders, and recommends technical approaches with minimal direction. Preferred experience includes SQL, Python, Databricks, Power BI, Power Apps, Power Automate, predictive modeling, and healthcare analytics.

Develops and leads business intelligence solutions, data models, reporting, exploratory analyses, and data governance initiatives. Communicates insights to stakeholders, drives BI adoption, improves data literacy, ensures data quality, and partners across Product, Underwriting, Actuarial, Finance, IT, Claims, and Analytics. The role also includes peer code reviews, project roadmaps, strategic data initiatives, stakeholder advising, and onboarding and developing team members.

Develop and maintain Power BI dashboards, reports, KPIs, and business systems supporting commissioning, quality, and infrastructure projects. Gather requirements, improve workflows and data quality, coordinate user acceptance testing, manage enhancement requests, and validate reporting accuracy. Collaborate with operational, engineering, construction quality, and regional stakeholders to support governance, project readiness, issue tracking, and data-driven decision-making. Create documentation, training materials, and communications for system releases and reporting changes.

Owns Power BI reporting and analytics for Digital, including internal dashboards, campaign pacing, client-facing intelligence products, contact data health, and data delivery monitoring. Builds DAX reporting logic, automated alerts, budget tracking, segmentation, benchmarking, and trend analysis. Partners with IT, Data Engineering, CRM, and audience teams while transitioning an externally developed platform in-house. Serves as the senior reporting subject matter expert for stakeholder and client-facing analytics.

The Senior Data Analyst will develop and improve Sigma dashboards, reporting, and business intelligence capabilities. Responsibilities include gathering stakeholder requirements, querying and analyzing complex datasets with SQL, improving data quality and governance, defining metrics, automating reporting processes, and partnering on Snowflake data modeling and warehouse improvements. The role also evaluates analytics tools, delivers actionable insights, and communicates findings to technical and non-technical audiences.

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.

Develop and maintain Power BI reports, dashboards, visualizations, semantic models, and analytics solutions. Translate business requirements into scalable technical solutions, optimize queries and data models, ensure reporting accuracy and performance, and support data governance. Serve as the primary liaison for business users, provide training and troubleshooting, manage tickets, and collaborate with Data and QA teams. The role also advances AI and machine learning capabilities, mentors colleagues, and contributes to automation, documentation, and code reviews.

Design, build, and maintain Power BI dashboards and data models using Snowflake and other cloud sources. Collaborate with data engineers/ETL teams, gather stakeholder requirements, implement DAX and Power Query transformations, ensure data governance and performance, and deliver analytics within Agile processes.

Design and build PerfectServe’s unified cloud data platform, including ingestion pipelines, integrations, data models, metrics, and consumer-facing data layers. Establish architecture, engineering, quality, and testing standards; enable safe extraction from production systems; partner with data users; and mentor data engineers. The role requires substantial cloud data platform experience, deep SQL, warehouse expertise, ELT, change-data-capture, AWS, modeling, orchestration, and data quality skills.

Lead and scale Runpod’s analytics and business intelligence function, managing analysts and BI practitioners while setting the analytics roadmap. Own core company metrics, consumption and marketplace analytics, self-service reporting, experimentation practices, and executive and board-level insights. Partner with Product, Finance, Engineering, Security, Supply, and Go-to-Market leaders to improve data quality, modeling, decision-making, and strategic outcomes.

The Business Intelligence Engineer analyzes complex internal and external data to solve business problems and deliver actionable insights to decision-makers. Responsibilities include integrating, analyzing, summarizing, and presenting data; conducting root cause analysis; using SQL, SAS, Databricks, and advanced Excel; and supporting data-driven business decisions. This is a remote role with occasional travel for training or meetings.

Leads enterprise Business Intelligence strategy, architecture, governance, security, and self-service analytics adoption. Architects solutions across Power BI, Tableau, SAP BusinessObjects, and Databricks; establishes semantic models, data standards, DevOps, CI/CD, and reporting performance practices. Partners with executives and technical teams to modernize analytics platforms, reduce manual reporting, and enable AI-ready decision-making. Mentors BI professionals and drives enterprise data literacy and analytics transformation.

Transforms complex retail and consumer data into business-ready datasets, scalable pipelines, reporting solutions, automation, and client deliverables. Designs data integration solutions in Unify, troubleshoots connector issues, explores AI-driven improvements, and partners with Product, Engineering, Client Development, Operations, and business stakeholders to define requirements and deliver scalable solutions.

Develop and support enterprise BI solutions, including dashboards, reports, governed datasets, data marts, and ETL/ELT processes. Translate business requirements into technical designs, perform data analysis and validation, troubleshoot production issues, and maintain documentation, governance, security, and data-quality standards. Lead-level candidates will guide technical decisions, mentor team members, and coordinate complex initiatives and incidents.

Develop and maintain Power BI reports, dashboards, apps, and reusable semantic models using SQL, DAX, and Power Query. Own day-to-day Power BI platform operations, including workspaces, publishing, licensing, refreshes, gateways, permissions, and content lifecycle. Translate stakeholder requirements into decision-ready reporting experiences, validate data and calculations, support testing and releases, troubleshoot issues, and coordinate with engineering and security teams. Coach report authors and promote governed, reliable self-service analytics.

Lead CX data intelligence initiatives using SQL, dashboards, analytical models, and AI/LLM techniques. Analyze customer journeys, operational metrics, churn risks, and retention indicators; develop insight agents and self-service reporting; define CX health metrics; and translate findings into strategic recommendations, process improvements, and experiments. Partner with operations, support, product, data, and engineering teams while maintaining data quality, governance, and documentation.