Medior Data Engineer

At AT&T we’re redefining the future of communication by connecting people to greater possibility - with expertise, simplicity, and inspiration. At the heart of our purpose lies a diverse workforce of 140,000 people and a culture that aspires to serve customers first, act boldly, move faster, and win as one. Our Product Development group, part of AT&T’s Technology Services (ATS) organization, is responsible for building software-based products, services, and platforms that our customers love and need. Harnessing technology and rebuilding software expertise, the team is inspiring simplicity with projects that deliver revenue and cost savings opportunities. AT&T continues to expand and modernize its high-volume data warehousing and analytics platforms. We are looking for a Medior Data Engineer to develop, support, and optimize ETL/ELT data pipelines in a high-volume data warehouse ecosystem. The ideal candidate brings solid, hands-on experience with data movement patterns and performance tuning, along with an interest in building domain understanding across telecommunications areas such as billing, product, customer, and operational interfaces.

Responsibilities

Develop, support, and optimize ETL/ELT data pipelines in a high-volume data warehouse ecosystem; Collaborate with lead and senior engineers to understand requirements and translate them into implementation tasks; Help develop and maintain ETL/ELT pipelines for large-volume enterprise data in Snowflake (or similar platforms); Support implementation of data loading frameworks (batch, incremental, CDC, micro-batch, and streaming where applicable) and operational observability; Help build and maintain automation for ingestion, transformation, testing, deployment, and monitoring across data lifecycle stages; Contribute to data quality checks, reconciliation controls, lineage capture, and metadata standards for production-grade reliability; Leverage AI-fueled coding (AIFC) practices to improve productivity, reduce defects, and accelerate delivery timelines; Participate in code reviews, follow best practices, and improve documentation and code quality through feedback and collaboration with senior engineers

Requirements

Hands-on experience with Python, Databricks, Snowflake, Kafka, Spark, and databases, including building batch and streaming pipelines, data modeling, and data quality practices; Hands-on experience with Python and databases (SQL/NoSQL) for building data solutions; Hands-on experience with Databricks and Spark for batch processing and basic streaming use cases; Hands-on experience with Snowflake for data warehousing and performance-aware development; Working experience with Kafka and real-time streaming data integration patterns; Working experience with cloud, Docker, and CI/CD practices; Working experience with AI-powered IDEs and tools (e.g., Visual Studio, GitHub Copilot, Windsurf, Cursor); Good analytical, problem-solving, and communication skills; 1+ years of data engineering experience, with some hands-on experience supporting, building, and operating ETL/ELT pipelines using Snowflake, Databricks, or similar data platforms and frameworks; Bachelor level degree or equivalent in Computer Science, or related field of study

Nice to have

Experience leveraging agentic solutions practices to improve productivity, reduce defects, and accelerate delivery timelines

Benefits

Annual company performance bonus; Wellness & leisure time contribution; Sickness compensation plan; Premium medical services; Family friendly benefits; Meal contribution; Extra days of vacation; Paid Time Off; Tuition Assistance; Medical and dental plans; Discounts; Training & Development