> Markdown version of [/jobs/ext/887980-lead-data-analysis](https://www.wearedevelopers.com/jobs/ext/887980-lead-data-analysis). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Lead Data Analysis - **Company:** AT&T Inc. - **Location:** Dallas, TX, United States - **Experience:** Expert - **Salary:** $130,700.0 - $196,100.0 - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Data Analysis, Information Systems, Databases, Data Governance, Extract Transform Load (ETL), Python (Programming Language), Microsoft SQL Server, Operational Databases, Oracle (Applications), SQL Databases, Transmission Control Protocol (TCP), Teradata SQL, Snowflake, Information Technology, Data Management - **Published:** June 10, 2026 - **Apply:** https://dejobs.org/x/x/8D38153A64254CB782197D000D3E0D47/job/ ## About the Role * Experience working in complex, multi-source enterprise data environments. * Strong knowledge of data quality, data governance, hierarchy management, and account or customer matching concepts. * Ability to analyze root causes, assess downstream impacts, and implement durable data quality improvements. * Experience supporting production data environments with a focus on stability, scalability, and issue resolution. * Demonstrated proficiency using SQL (Snowflake preferred but SQL Server, Oracle, and Teradata are also relevant), analytical or data tools such as Python to analyze data, validate outputs, and resolve complex data issues; AI tool experience is a plus. * Strong collaboration, communication, and prioritization skills across business, analytics, and technology teams. * Experience supporting automation or AI/ML-enabled data maintenance initiatives is a plus. Job Contribution: Recognized as an experienced professional with broad and in-depth knowledge, this role resolves complex data issues, leads significant initiatives with strategic autonomy, and influences decisions that improve enterprise data quality and operational performance. The position collaborates across teams, supports long-term data improvements, and may mentor less experienced staff. Supervisor: No TCP Career Step Differentiator: Manages complex data movement and storage from multiple sources, and high-level analytics to solve business problems. Education/Experience: Bachelor's degree preferred in Computer Science, Mathematics, Information Systems, or a related field. Typically requires 5+ years of relevant experience in data analysis, data quality, data management, or related disciplines. Certifications may be required in some areas. ## Description * Collect, process, cleanse, and validate data from multiple internal and external sources. * Define, maintain, and improve data rules, mappings, transformations, and interface requirements. * Identify, investigate, and resolve data discrepancies across systems to improve accuracy, consistency, and reliability. * Monitor data quality, hierarchy integrity, and matching outcomes; recommend scalable corrective actions and logic improvements. * Support production data processes across the lifecycle, including pre-production validation, production issue resolution, and post-production monitoring. * Partner with business, analytics, and technology teams to ensure trusted data supports reporting, segmentation, and decision-making. * Contribute to automation and advanced data quality initiatives that reduce manual rework, operational risk, and downstream escalations. * Translate data issues into business impact and prioritize improvements that enhance efficiency, accuracy, and scalability. ## Related Videos - [From Messy Queries to Scalable Systems - How Data Engineering actually works](https://www.wearedevelopers.com/videos/100203-from-messy-queries-to-scalable-systems-how-data-engineering-actually-works) - [Kubernetes and Microservices with Multi-Model Databases](https://www.wearedevelopers.com/videos/382-kubernetes-and-microservices-with-multi-model-databases) - [How Cisco embraced a DevOps culture within its network engineering team](https://www.wearedevelopers.com/videos/99-how-cisco-embraced-a-devops-culture-within-its-network-engineering-team) - [OLTP in the Lakehouse: Redefining Data for AI Workloads](https://www.wearedevelopers.com/videos/2038-oltp-in-the-lakehouse-redefining-data-for-ai-workloads) - [Fault Tolerance and Consistency at Scale: Harnessing the Power of Distributed SQL Databases](https://www.wearedevelopers.com/videos/1146-fault-tolerance-and-consistency-at-scale-harnessing-the-power-of-distributed-sql-databases) - [Hacking AI at the Edge of the Indian Ocean](https://www.wearedevelopers.com/videos/100177-hacking-ai-at-the-edge-of-the-indian-ocean) ## Related Articles - [Top Big Data Technologies That You Need to Know](https://www.wearedevelopers.com/magazine/108-top-big-data-technologies-that-you-need-to-know) - [What Industries Outside of AI Are Hiring The Most AI Experts?](https://www.wearedevelopers.com/magazine/98-what-industries-outside-of-ai-are-hiring-the-most-ai-experts) - [Coffee with Developers - Maria Apazoglou - Making AI understandable for all in production](https://www.wearedevelopers.com/magazine/475-coffee-with-developers-maria-apazoglou-making-ai-understandable-for-all-in-production) - [Highest Paying Tech Companies for Developers](https://www.wearedevelopers.com/magazine/220-highest-paying-tech-companies-for-developers) - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [Making Data Warehouses Fast: A Developer’s Story](https://www.wearedevelopers.com/magazine/107-making-data-warehouses-fast-a-developer-s-story)