Lead Advanced Analytics

AT&T AT&T · Telecom · Dallas, TX +1

This role focuses on Support activities reporting and analytics, responsible for reporting KPI and operational detail. It involves working with partners to ensure data availability, monitoring performance, and creating/maintaining reports in various in-suite tools. The role also involves designing, building, and maintaining scalable data pipelines, developing curated datasets and data models, applying data architecture best practices, implementing data quality checks, optimizing data performance, and collaborating with stakeholders to translate requirements into data solutions.

What you'd actually do

  1. Design, build, and maintain scalable batch and/or streaming data pipelines across multiple source systems (APIs, databases, Engineering Tools and event streams).
  2. Develop curated datasets and data models that support analytics, reporting, and operational use cases.
  3. Apply data architecture best practices (ingestion patterns, schema evolution, data contracts, lake/warehouse organization).
  4. Implement data quality checks, observability/monitoring, lineage, and SLAs; troubleshoot pipeline issues end-to-end.
  5. Optimize data performance and cost (partitioning, clustering, file formats, query tuning, compute sizing)

Skills

Required

  • 5-7 years (or equivalent) experience in data engineering, analytics engineering, or backend development with significant data work.
  • Advanced SQL and proficiency in at least one language (Python, Java, or Scala).
  • Hands-on experience with orchestration and transformation tools (e.g., Datbricks, Snowflake, Airflow, dbt, Spark, or similar).
  • Experience with cloud data ecosystems (AWS/GCP/Azure) and data storage/compute services (data lake/warehouse).
  • Strong understanding of data modeling (dimensional modeling and/or other modern modeling approaches).
  • Solid engineering practices: Git, code reviews, testing, CI/CD, and clear documentation.