About T-Mobile:
T-Mobile US, Inc. (NASDAQ: TMUS), headquartered in Bellevue, Washington, is America’s supercharged Un-carrier, connecting millions through its strong nationwide network and flagship brands, T-Mobile and Metro by T-Mobile. Customers benefit from an unmatched combination of value, quality, and exceptional service experience.
About TMUS Global Solutions:
TMUS Global Solutions is a world-class technology powerhouse accelerating the company’s global digital transformation. With a culture built on growth, inclusivity, and global collaboration, the teams here drive innovation at scale, powered by bold thinking.
TMUS India Private Limited operates as TMUS Global Solutions.
Senior Engineer, Software – Data Ingest Engineering
About the Role:
Data Ingest Engineering is the central engineering team building the Enterprise Unified Ingestion Framework for the future that delivers the right data, at the right speed, with the right governance — to every consumer: a T-Mobile customer opening an app, a business analyst asking a natural language question, or an AI agent executing autonomously.
As a Senior Engineer, Software, you will be a hands-on builder and technical lead at the center of that mission — designing and delivering the batch and streaming framework for data pipelines, stores, and APIs that make T-Mobile’s data consumable at any speed, for any consumer. We pride ourselves on fostering a culture of innovation, agile ways of working, and transparency in everything we do. Join us in embodying the spirit of the Un-carrier and make a tangible impact!
What You’ll Do:
- Design and implement high-throughput, event-driven architectures to power near real-time data pipelines for ingesting into Azure + Databricks Lakehouse
- Build cloud-native data pipelines to support batch ingest workloads
- Configure Unity Catalog by designing Bronze/Silver/Gold medallion architecture and optimize for centralized data governance, fine-grained access control, and end-to-end lineage tracking across Databricks workspaces
- Drive engineering excellence by setting standardized DevOps practices and optimizing data engineering code for performance
- Identify and design solutions to potential data processes that can be improved with automation
- Partner with domain teams to onboard new capability use cases, mentor engineers, and contribute to reusable blueprints and reference implementations.
What You’ll Bring:
- 7+ years of software engineering experience focused on data infrastructure and backend systems.
- Hands-on experience with the Microsoft Azure data platform — Azure Data Factory, Event Hubs, Blob Storage, ADLS Gen2, and Azure DevOps for orchestration and CI/CD
- Production experience with Azure Databricks and Delta Lake
- Production experience with PySpark for distributed data processing and transformation.
- Streaming frameworks (Kafka or comparable) for real-time data paths including CDC and incremental batch patterns.
- Strong communication skills with the ability to influence senior stakeholders and lead technical decisions across global teams.
Must Have Skills:
- Data Platform Architecture (Lakehouse, Delta Lake, Azure Databricks)
- Kafka / Streaming Frameworks
- Strong SQL and Python Proficiency
- Experience with Cloud Native Tools
Nice-to-Have:
- Building data infrastructure for AI use cases
- Prior experience in large-enterprise data integration or platform engineering environments
- Prior experience in enterprise platform migrations.
