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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Lead Data Analysis - **Company:** AT&T Inc. - **Location:** Roswell, GA, United States - **Experience:** Expert - **Salary:** $100,000.0 - $115,000.0 - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Amazon Web Services, Business Analytics Applications, Data Analysis, Microsoft Azure, Cloud Computing, Information Systems, Databases, Data Architecture, Information Engineering, Data Governance, Data Integration, Extract Transform Load (ETL), Data Visualization, Data Warehousing, DevOps, Python (Programming Language), Machine Learning, Meta-Data Management, Power BI, Cloud Services, DataOps, Tableau (Software), Google Cloud, Sql Optimization, Snowflake, Generative AI, Data Strategy, Information Technology, Data Lineage, Data Analytics, Data Management, Data Pipelines, Databricks - **Published:** October 15, 2026 - **Apply:** https://www.jofdav.com/jobs/60111305-lead-data-analysis ## About the Role * Bachelor's degree in computer science, information systems, data analytics, mathematics, statistics, engineering, or a related field is preferred. * 5+ years of experience in data analysis, business intelligence, data engineering, or a related analytics role. * Demonstrated experience leading complex analytical initiatives and communicating findings to technical and nontechnical stakeholders., * Advanced SQL skills and experience working with large-scale relational and analytical databases. * Experience with business intelligence and visualization platforms such as Power BI, Tableau, or similar tools. * Strong Python programming skills and experience with relevant data-analysis libraries. * Experience designing, developing, and supporting ETL/ELT pipelines and modern data architectures. * Experience with cloud analytics and data platforms such as Databricks, Snowflake, Microsoft Azure, AWS, or Google Cloud. * Knowledge of machine learning, generative AI, AI-assisted analytics, and data science concepts. * Experience with data governance, metadata management, data lineage, and data quality frameworks. * Familiarity with Agile delivery methods and DevOps or DataOps practices. * Relevant certifications in analytics, cloud technologies, Databricks, Snowflake, AI, or related disciplines are a plus. Technical Skills and Modern Analytics Technologies * Advanced SQL and Python * Statistical analysis and analytical problem-solving * Power BI, Tableau, or comparable visualization tools * Data modeling and data architecture * ETL/ELT pipelines and data integration * Data warehousing and enterprise reporting * Cloud data platforms, preferably Databricks and/or Snowflake * Machine learning, generative AI, and AI-assisted analytics * Data governance, metadata management, data lineage, and data quality * Agile delivery and DevOps/DataOps practices ## Description This is a full-time onsite role based in the location(s) posted and is performed from the designated work location five days per week. No relocation is offered., The Lead Data Analyst is a strategic data expert who transforms complex data into actionable insights that support informed decision-making and operational excellence. This role leads the collection, integration, analysis, governance, and visualization of data from multiple enterprise sources while promoting data quality, accuracy, consistency, and reliability. The ideal candidate combines advanced analytical expertise with experience in modern data engineering, cloud analytics, and AI-enabled technologies. This individual develops scalable reporting solutions, advanced analyses, and predictive insights that address complex business needs. Working closely with business stakeholders, technology teams, and senior leaders, the Lead Data Analyst identifies opportunities, solves complex business problems, and enables data-informed decision-making across the organization. As a recognized subject matter expert (SME), the Lead Data Analyst provides technical leadership for large-scale analytics initiatives, mentors team members, contributes to data strategy, and advances the adoption of modern analytics platforms and emerging technologies. Key Roles and Responsibilities: Responsibilities may include, but are not limited to: * Data Collection and Preparation: Collect, integrate, preprocess, and cleanse data from multiple sources to make it accurate, consistent, and ready for analysis. * Data Analysis and Interpretation: Apply statistical and analytical methods to identify patterns, trends, risks, and opportunities, and translate findings into actionable recommendations. * Reporting and Visualization: Develop accurate, clear, and compelling dashboards, visualizations, and reports that communicate findings effectively to technical and nontechnical stakeholders. * Data Quality and Discrepancy Resolution: Identify and resolve data discrepancies across systems and platforms. Establish quality controls, conduct audits, and monitor data to maintain reliability. * Data Integration: Design, develop, and support scalable ETL/ELT pipelines that integrate data from multiple enterprise sources. * Business Intelligence: Develop and maintain enterprise reporting and business intelligence solutions using tools such as Power BI, Tableau, or similar platforms. * Advanced Analytics: Apply appropriate statistical, predictive, machine-learning, and AI-assisted analytical methods to address complex business questions. * Data Governance: Support data governance, metadata management, data lineage, and data quality practices across relevant data domains. * Stakeholder Collaboration: Partner with business and technology teams to define analytical requirements, establish success measures, and deliver solutions aligned with organizational objectives. * Technical Leadership: Lead complex analytics initiatives, contribute to architectural and platform decisions, mentor less-experienced team members, and promote analytics best practices. * Modernization: Evaluate emerging technologies and support the adoption of modern cloud data platforms, analytical tools, and DataOps practices. Job Contribution An experienced professional recognized as an expert who applies broad and in-depth knowledge to resolve complex analytical and data-related challenges. Leads significant projects with a high degree of strategic autonomy and influences technical and business decisions. Develops and implements long-term plans that affect the organization, mentors less-experienced employees, and frequently collaborates with senior leaders. Supervisory Responsibility: No direct supervisory responsibility. Career Step Differentiator Leads enterprise-scale data integration, governance, advanced analytics, and business intelligence initiatives spanning multiple platforms and data domains. Serves as an SME for analytics, enterprise reporting, cloud data platforms, AI-enabled insights, and data management practices. Contributes to data strategy, advances modernization efforts, and provides technical leadership for complex, business-critical analytical solutions.