Sr Engineer, Data

T-Mobile; Hyderabad; On-site; INR 11,429,000 - 20,000,000; Full time

Job summary

T-Mobile US, Inc. is seeking a Senior Engineer, Data to design and deliver scalable data architectures for enterprise analytics and customer intelligence use cases. You will work across on-premises, cloud, and hybrid environments and lead development of data pipelines and platforms.

You will mentor engineers, drive architectural maturity, and collaborate with analytics teams to enable data-driven decision-making and personalization.

Qualifications

• Bachelor's degree or equivalent practical experience.
• 9-12 years hands-on experience in data engineering.
• Experience migrating data solutions across cloud platforms.
• Strong leadership and mentoring capabilities.

Responsibilities

• Design and deliver scalable data architectures for enterprise analytics.
• Architect data platforms across on-premises, cloud, and hybrid environments.
• Lead large-scale data processing with Databricks and Spark technologies.
• Mentor engineers and drive architectural maturity across teams.
• Collaborate with analytics and data science teams to enable personalized insights.

Skills

Python

SQL

Databricks PySpark

Spark SQL

Cloud platforms

REST APIs

AI-assisted development

NL-to-SQL with Databricks Genie

Unity Catalog

Data modeling

Education

Bachelor's Degree in CS/CE or related field

Tools

Databricks

Snowflake

Apache Spark

Postman

Swagger/OpenAPI

Unity Catalog

Job description

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.

About the Role

Sr Engineer, Data designs and delivers scalable data architectures and advanced data engineering solutions across on-premises, cloud, and hybrid platforms to support enterprise analytics and customer intelligence use cases. This role partners closely with data engineers, architects, and analytics teams to analyze, design, and optimize data warehouse and analytics solutions that power personalization and data-driven decision-making within the customer data platform. The Sr Engineer provides hands-on technical leadership, mentors engineers, and drives the evolution of modern data architectures. Success is measured by solution effectiveness, scalability, performance, and growth in team capability and architectural maturity.

What You’ll Do

• Design and develop advanced data engineering solutions that enable data pipelines, visualization, and analytical tools
• Architect and implement scalable data platforms across on-premises, cloud, and hybrid environments
• Build, optimize, and operate complex batch and real-time and near real-time streaming data pipelines
• Build, optimize, and operate low-latency, sub-second APIs on highly scalable, fault-tolerant architectures.
• Design and maintain high-throughput data pipelines to support agentic AI workloads and real-time multi-agent MCP orchestration.
• Build and maintain enterprise-scale Graph Databases that power organizational knowledge graphs and connected data experiences.
• Perform data wrangling, exploration, and discovery across heterogeneous data sources to generate insights
• Lead development of large-scale data processing solutions using Databricks and Spark technologies
• Design and optimize relational, NoSQL, and analytical data models
• Contribute to team knowledge sharing and advancement of data engineering standards and capabilities
• Mentor engineers to strengthen technical skills, delivery quality, and professional growth
• Support project definition activities including estimation, planning, and scoping in partnership with management

What You’ll Bring

• Bachelor’s Degree in Computer Science, Computer Engineering, or a related field, or equivalent practical experience
• 9-12 years of hands-on experience designing, building, and supporting data engineering solutions
• Strong experience developing and migrating data solutions across cloud platforms
• Demonstrated technical leadership and mentoring experience
• Strong analytical and problem-solving skills applied to complex data challenges
• Ability to manage multiple concurrent initiatives with strong organizational and prioritization skills
• Passion for learning and applying new data and platform technologies

Must Have Skills

Core Data Engineering & Platforms

• Advanced experience designing and building complex data pipelines using Python and SQL
• Strong experience with cloud platforms and services, including:
• Databricks with PySpark, Spark SQL, and Scala Spark, including cluster configuration, autoscaling, and performance optimization (e.g., Photon)
• Snowflake data warehousing, including schema design (star/snowflake), query optimization, and cost/performance tuning
• Expertise in SQL, NoSQL, and relational database design and development

APIs, Streaming & Integration

• Proficiency designing and consuming RESTful APIs with secure authentication and authorization (OAuth 2.0, JWT, API keys)
• Experience using Postman and Swagger/OpenAPI for API testing, documentation, and validation
• Working knowledge of message queuing, stream processing, and highly scalable big-data data stores
• Advanced knowledge of data pipeline development using Python and experience with languages such as SQL, DAX, Java, Scala, and/or Go
• Experience performing root-cause analysis and using technology to solve complex business problems
• Experience adopting AI-assisted development tools and building AI-powered agents or agentic workflows to automate engineering tasks, accelerate delivery, and enhance data platform capabilities
• Experience with NL-to-SQL query generation using Databricks Genie and Snowflake Cortex to enable natural language access to data assets
• Hands-on experience with Unity Catalog for data governance, fine-grained access control, and end-to-end data lineage
• Experience developing AI-assisted dbt models, including AI-generated transformation logic, automated documentation, and intelligent testing
• Familiarity with AI-powered data quality tools for automated profiling, anomaly detection, and pipeline observability

Nice to Have

• Experience with Iceberg table design and optimization
• Experience with Unity Catalog governance and security
• Cloud platform certifications such as Azure Certified Solutions Architect, Azure Cloud Practitioner, or MCSA
• Experience contributing to enterprise data governance, security, or compliance initiatives
• Experience with ML feature platforms (e.g., Feast, Tecton, or Databricks Feature Store) and vector database engineering (e.g., Pinecone, Weaviate, pgvector)
• Experience designing and operating streaming AI pipelines and applying MLOps practices to data engineering workflows
• Exposure to end-to-end ML pipeline ownership and real-time AI inference plumbing in production environments