Engineer, Data [T500-20281]

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.

About the Role :

The Data Engineer is responsible for designing and building the infrastructure required for efficient extraction, transformation, and loading (ETL) of data from various sources using SQL, Azure, and AWS big data technologies. The role includes identifying and implementing improvements in processes such as automation, optimization of data delivery, and scalability enhancements.

The engineer collaborates with cross-functional teams to ensure the data infrastructure is scalable, reliable, and optimized for analytics and data science use cases. This position is instrumental in delivering high-quality data pipelines that enable better decision-making and operational efficiency across the organization.

What You’ll Do :

Create and maintain scalable and robust data pipeline architectures, visualization tools, and analytics platforms.

Assemble large and complex data sets that meet both functional and non-functional business requirements.

Build analytics tools leveraging pipeline data to generate insights for business performance, customer acquisition, and operational efficiency.

Partner with internal stakeholders to resolve technical issues and support evolving data infrastructure needs.

Develop internal tools for use by analytics and data science teams to improve data performance and usability.

Collaborate with analytics teams to increase overall system functionality and data accessibility.

Participate in process improvements, automation, and infrastructure redesign projects.

Perform additional duties and cross-functional projects as needed.

What You’ll Bring :

Bachelor’s degree in Computer Science, Information Systems, Informatics, Statistics, or related quantitative discipline — or equivalent experience.

2–4 years of experience in data engineering roles.

Experience with designing and optimizing big data pipelines, architecture, and datasets.

Hands-on experience in SQL and at least one of the following languages : Python, Java, Scala, Go, or DAX.

Strong problem-solving skills with the ability to perform root cause analysis.

Familiarity with cloud environments (e.g., Azure, AWS).

Excellent communication and collaboration abilities.

Must Have Skills : Data Engineering

SQL, Python, Automation, RDBMS, Snowflake, NoSQL, PowerBI, ETL, Cloud Platform

Nice To Have :

Experience with dashboarding or BI tools.

Exposure to machine learning or predictive analytics use cases.

Familiarity with data governance and privacy principles.