Lead Data Analysis

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.

Role Overview

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.

Education and Experience

• •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.

Preferred Qualifications

• •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



Our Lead Data Analysis jobs earn between $116,700.00 - $196,100.00 USD Annual. Not to mention all the other amazing rewards that working at AT&T offers. Individual starting salary within this range may depend on geography, experience, expertise, and education/training.
 Joining our team comes with amazing perks and benefits:

• •Medical/Dental/Vision coverage
• •401(k) plan
• •Tuition reimbursement program
• •Paid Time Off and Holidays (based on date of hire, at least 23 days of vacation each year and 9 company-designated holidays)
• •Paid Parental Leave
• •Paid Caregiver Leave
• •Additional sick leave beyond what state and local law require may be available but is unprotected
• •Adoption Reimbursement
• •Disability Benefits (short term and long term)
• •Life and Accidental Death Insurance
• •Supplemental benefit programs: critical illness/accident hospital indemnity/group legal
• •Employee Assistance Programs (EAP)
• •Extensive employee wellness programs
• •Employee discounts up to 50% off on eligible AT&T mobility plans and accessories, AT&T internet (and fiber where available) and AT&T phone

Weekly Hours:

40

Time Type:

Regular

Location:

Alpharetta, Georgia, Dallas, Texas

Salary Range:

• $116,700.00 - $196,100.00
• AT&T and its subsidiaries are committed to equal employment opportunity. All hiring, promotion, and other employment decisions remain merit-based and free from discrimination on the basis of race, color, religion, religious creed, national origin, ancestry, age, sex, sexual orientation, gender, gender identity, gender expression, physical disability, mental disability, pregnancy, medical condition, genetic information, marital status, citizenship status, military status, veteran status, or any other characteristic protected by federal, state, or local laws. In addition, A