Lead 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 an advanced Lead Data Engineer to architect, design, build, and optimize enterprise-scale ETL/ELT data pipelines in a high-volume data warehouse ecosystem. The ideal candidate brings deep technical expertise in large-scale data movement patterns and performance tuning, along with functional understanding of telecommunications domains such as billing, product, customer, and operational interfaces.

Deep expertise in Python, Databricks, Snowflake, Kafka, Spark, and databases, including building scalable batch and streaming pipelines, data modeling, and data quality practices.

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  Collaborate cross-functionally with product and data engineering teams to scope, define, and translate complex business needs into technical requirements.

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  Design, develop, and maintain scalable ETL/ELT pipelines for large-volume enterprise data in Snowflake (or similar platforms).

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  Implement robust data loading frameworks (batch, incremental, CDC, micro-batch, and streaming where applicable) with clear SLAs and operational observability.

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  Build reusable automation for ingestion, transformation, testing, deployment, and monitoring across data lifecycle stages.

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  Build and enforce data quality checks, reconciliation controls, lineage capture, and metadata standards for production-grade reliability.

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  Partner with architecture, product, operations, and governance teams to ensure secure, compliant, and high-quality data products.

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  Leverage AI-fueled coding (AIFC) practices to improve productivity, reduce defects, and accelerate delivery timelines.

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  Participate in code reviews, contribute to best practices, and mentor peers on data engineering technologies and frameworks.

• Deep experience with Python and databases (SQL/NoSQL) for building production-grade data solutions.

• Deep experience with Databricks and Spark for large-scale batch and streaming processing.

• Deep experience with Snowflake for data warehousing, performance optimization, and secure data access.

• Deep experience with Kafka and real-time streaming data integration patterns.

• Deep experience with cloud, Docker, and CI/CD practices for scalable, reliable deployments.

• Deep experience with AI-powered IDEs and tools (e.g., Visual Studio, GitHub Copilot, Windsurf, Cursor).

• Exceptional analytical, problem-solving, and communication skills.

Bachelor level degree or equivalent in Computer Science, or related field of study. 

This is a hybrid-flex worker position where our preference is for you to be present with your team in the office at least 2 days per week.   

It is the policy of AT&T to provide equal employment opportunity (EEO) to all persons regardless of age, color, national origin, citizenship status, physical or mental disability, race, religion, creed, gender, sex, sexual orientation, gender identity and/or expression, genetic information, marital status, status with regard to public assistance, veteran status, or any other characteristic protected by federal, state or local law. In addition, AT&T will provide reasonable accommodations for qualified individuals with disabilities. AT&T is a fair chance employer and does not initiate a background check until an offer is made.