Jobs / United States / AT&T Services INC
Senior Data Analysis
AT&T Services INC · 🇺🇸 2 Locations
Sponsorship verdict
Sponsorship possible
One solid signal, not two — worth applying, and worth asking about sponsorship early.
- Employer is on a government sponsor recordThe US Department of Labor certified 393 H-1B/E-3 labor condition applications for this employer between Oct 2025 and Jun 2026 (latest Jun 2026) — the step every H-1B hire needs first. USCIS also records 80 H-1B approvals in FY2023. Source: LCA disclosure data (US Department of Labor (OFLC)).
- The posting doesn’t mention sponsorshipSilence isn’t a refusal — ask the recruiter before investing much time.
- No salary bar for this routeH-1B has no fixed salary bar: the employer must pay at least the prevailing wage for the role and area. Cap-subject employers enter a lottery weighted by wage level. Source: https://www.federalregister.gov/documents/2025/12/29/2025-23853/weighted-selection-process-for-registrants-and-petitioners-seeking-to-file-cap-subject-h-1b, rules effective 2026-02-27.
- What AT&T Services INC paid sponsored hires in similar roles3 certified filings for “PRINCIPAL DATA ANALYSIS” (Data Scientists) in GA: $150k–$164k, median $164k. Most were filed at wage level IV (100%) — 4 lottery entries, ≈61% projected selection odds for cap-subject employers. Source: US Department of Labor LCA disclosure data (Oct 2025 – Jun 2026).
- Confirmed live todayWhen a source last listed this job as open.
US H-1B: cap-subject employers enter a lottery weighted by wage level — Level I gets 1 entry, Level IV gets 4 (DHS projected selection odds ≈15% at Level I to ≈61% at Level IV). Universities and non-profit research employers are cap-exempt. The $100,000 fee for new petitions from abroad is currently blocked by a court order (appeal pending).
A verdict summarises public evidence; it is not legal advice and never a guarantee — the employer and the immigration authority decide. Sign in to factor in where you can already work.
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Sponsor Radar — AT&T Services INC
The US Department of Labor certified 393 H-1B/E-3 labor condition applications for this employer between Oct 2025 and Jun 2026 (latest Jun 2026) — the step every H-1B hire needs first. USCIS also records 80 H-1B approvals in FY2023. Source: LCA disclosure data (US Department of Labor (OFLC)).
Past sponsorship or register membership never guarantees sponsorship for this vacancy or for you. Full Sponsor Radar for AT&T Services INC →
About the role
This position requires office presence of a minimum of 5 days per week and is only located in the location(s) posted. No relocation is offered. Overall Purpose: Sr. Data Analysis professionals support the accuracy, integrity, and usability of enterprise data across multiple business applications and repositories. This role focuses on data collection, processing, validation, quality monitoring, discrepancy investigation, and production support to help maintain trusted data foundations. The position contributes to reliable downstream reporting, analytics, and business decision-making by supporting consistent and dependable data operations. Role Summary: This role is centered on supporting enterprise data quality and operational reliability rather than owning dashboards or visualization deliverables. The Sr. Data Analysis position applies established data rules, investigates issues, supports integrations and production processes, and contributes to continuous improvement efforts in partnership with business, analytics, and technology teams. Key Responsibilities: • Collect, process, cleanse, and validate data from multiple internal and external sources. • Apply and maintain established data rules, mappings, transformations, and interface requirements. • Investigate and resolve data discrepancies across systems to improve accuracy, consistency, and reliability. • Monitor data quality results, hierarchy integrity, and matching outcomes; escalate patterns and recommend improvements when appropriate. • Support production data processes, including validation activities, issue triage, and post-production follow-up. • Partner with business, analytics, and technology teams to support trusted data for reporting and operational decision-making. • Use SQL and other analytical tools to analyze data, validate outputs, and support issue resolution. • Contribute to process improvements and automation efforts that reduce manual rework and improve data reliability. Qualifications: • Experience working in multi-source data environments with attention to data accuracy and consistency. • Knowledge of data quality, data governance, hierarchy management, and account or customer matching concepts. • Ability to investigate root causes, assess downstream impacts, and support corrective actions. • Experience supporting production data processes with a focus on validation, issue resolution, and operational stability. • Working knowledge of SQL (Snowflake preferred but SQL Server, Oracle, and Teradata are also relevant). Experience with 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 organizational skills across business and technical teams. • Experience contributing to automation or data quality improvement initiatives is a plus. Job Contribution: Recognized as an experienced professional with strong working knowledge in the field, this role independently handles moderately complex data issues, supports key data quality and operational initiatives, and contributes to improvements in enterprise data reliability and performance. The position works within established priorities, collaborates across teams, and may provide guidance to less experienced staff. Supervisor: No TCP Career Step Differentiator: Supports data movement, validation, and quality activities across multiple sources while applying analytical methods to solve defined business and operational problems. Education/Experience: • Bachelor’s degree preferred in Computer Science, Mathematics, Information Systems, or a related field. • Typically requires 3-5 years of relevant experience in data analysis, data quality, data management, or related disc