Sr Engineer, Data [T500-28676]

TMUS Global Solutions; Hyderabad; On-site; INR 1,200,000 - 2,400,000; Full time

Job summary

TMUS Global Solutions is seeking a Data Engineer (Level III) to design, build, and operate production-grade data pipelines powering P&SC intelligence across device supply chain and logistics. You will own reliability, KTLO, and data quality while collaborating with analysts to implement transformations and business rules.

Role emphasizes hands-on engineering within a squad, adherence to Fabric IQ standards, and migration of legacy platforms.

Qualifications

• 5-8 years of data engineering experience delivering production-grade pipelines.
• Strong Python, PySpark, Spark SQL, and T-SQL skills.
• Expert-level data modelling across 3NF, Kimball, and Data Vault 2.0.
• Proficient in Azure Data Factory for ELT/ETL pipelines.
• Hands-on Azure Databricks with Delta Lake and Unity Catalog.
• Experience with dbt, SQL validation, and data quality checks.
• DevOps for data pipelines: Git, CI/CD, automated tests.
• Agile or Scrum certification or equivalent.
• Ability to work independently on complex problems.

Responsibilities

• Design and build production-grade data pipelines across ingestion, bronze to gold layers.
• Own pipeline KTLO including monitoring, alerting, incidents, and reliability.
• Implement ingestion patterns: batch, API, and event-driven streaming.
• Apply medallion architecture and Fabric IQ standards in builds.
• Collaborate on data transformations and data quality per requirements.
• Participate in design reviews aligning with Databricks and Fabric standards.
• Support migration from legacy platforms like SCOpsBI SQL Server and SAP.
• Write and maintain pipeline documentation including lineage and SLAs.
• Contribute to DevOps and reliability practices: CI/CD, testing, runbooks.
• Mentor junior data engineers in the squad.

Skills

Python

PySpark

Spark SQL

T-SQL

Azure Data Factory

Azure Databricks

dbt

SQL

Data modelling

Data quality

Git

CI/CD

Agile/Scrum

Tools

Azure Data Factory

Azure Databricks

dbt

Git

CI/CD

Snowflake

Kafka

Azure Event Hub

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.

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

The Data Engineer (Level III) designs, builds, and operates the data pipelines and lakehouse data products that power P&SC intelligence across device supply chain, reverse logistics, procurement, network supply chain, and real-time control tower capabilities. Operating within a squad focused on a specific SC domain or cross-cutting platform function, the Data Engineer is a hands-on technical contributor who builds to production quality, owns pipeline reliability and KTLO, and contributes to the engineering standard of the team.

What You’ll Do

• Design and build production-grade data pipelines spanning source ingestion, bronze landing, silver transformation, and gold-layer data product delivery within the squad's domain scope.
• Own pipeline KTLO (Keep the Lights On) for assigned data products, including monitoring, alerting, incident response, and ongoing reliability improvements.
• Implement data ingestion patterns for assigned source systems including batch file ingestion, API-based ingestion, and event-driven streaming (Kafka, Azure Event Hub) depending on squad scope.
• Apply medallion architecture (bronze, silver, gold) and Fabric IQ certification standards consistently across all data product builds.
• Collaborate with System Analysts to implement field-level transformations, business rule logic, and data quality checks as specified in product requirements documentation.
• Participate in and contribute to pipeline design reviews, ensuring solutions align with the organization's Databricks and Fabric engineering standards.
• Support the migration and deprecation of legacy platforms including SCOpsBI SQL Server and SAP boundary systems, following the organization's extract, validate, rebuild, cutover, and decommission pattern.
• Write and maintain comprehensive pipeline documentation including data lineage, transformation logic, SLA definitions, and dependency maps.
• Contribute to the organization's DevOps and engineering reliability practices including CI/CD pipeline setup, testing frameworks, and incident runbooks.
• Support and collaborate with junior data engineers within the squad, sharing knowledge and providing guidance on day-to-day engineering tasks.

Must Have Skills

• 5-8 years of data engineering experience with a track record delivering production Grade data pipelines in enterprise environments.
• Strong experience on Python, PySpark, Spark SQL, and T-SQL
• Strong Proficiency in Azure Data Factory for building and maintaining ELT/ETL pipelines, including parameterization, triggers, linked services, and error handling
• Hands-on experience with Azure Databricks including Delta Lake, Unity Catalog, and workflow orchestration.
• Hands-on experience with dbt (Data Build Tools) writing models, tests, sources, and documentation within an established project structure
• Solid SQL skills for data validation, transformation logic, and ad-hoc source system analysis.
• Expert-level data modelling skills across 3NF, Dimensional (Kimball), and Data Vault 2.0 patterns
• Strong understanding of data quality frameworks, including implementing checks, alerting on anomalies, and maintaining SLA-compliant pipeline health.
• Experience with DevOps practices for data pipelines including version control (Git), CI/CD, and automated testing.
• Agile or Scrum practitioner certification or equivalent
• Ability to operate with moderate independence on complex technical problems, escalating appropriately and maintaining clear technical documentation.

Nice to Have

• Experience with real-time streaming technologies including Kafka, Azure Event Hub, Delta Live Tables, or Spark Structured Streaming.
• Working experience with Snowflake — table design, query performance tuning, views, stored procedures, and data loading patterns (Snow pipe, COPY INTO)
• Experience with enterprise batch scheduling and orchestration tools such as Control-M or Autosys is a plus.
• Experience with real-time streaming technologies including Kafka, Azure Event Hub, Delta Live Tables, or Spark Structured Streaming.
• Experience with Microsoft Fabric or Azure Synapse Analytics; familiarity with Fabric IQ and One Lake is a plus.
• Background in supply chain, reverse logistics, procurement, or network infrastructure data domains
• Experience working within Agile delivery frameworks — including PI planning, sprint-level technical governance, and cross-squad dependency management
• Familiarity with AI-assisted development tools such as GitHub Copilot or Claude, and experience integrating AI/ML-ready data preparation into ETL/ELT pipeline design
• Working knowledge of SOX and USGCI compliance requirements as they apply to enterprise data platform design and deployment
• Microsoft Azure certifications — DP-203, AZ-305, DP-900, or the Microsoft Fabric Analytics Engineer Associate
• Python development skills beyond PySpark, including utility scripting and framework contributions.