Senior Data Engineer

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 the Role

As a Senior Data Engineer, you will design, build, and operate trusted data products that serve enterprise business customers across Finance, Risk, and Operations. You will report into the US-based team and work directly with managers and Technical Product Owners translating business context into engineering decisions and delivering production-grade data products with limited day-to-day direction. You will be measured on the quality of the data product, the trust customers place in it, and your judgment in balancing speed for the immediate need against durability for the enterprise.

We pride ourselves on encouraging a culture of innovation, agile ways of working, and transparency in all we do. Join us in embodying the spirit of the Un-carrier and make a tangible impact.

What You'll Do:

- Own data products end-to-end from ingestion through curated consumption layers feeding business reporting, downstream models, and analytics teams.
- Build and maintain pipelines on modern Lakehouse platforms (Delta Lake, Unity Catalog, PySpark, SQL) and cloud data warehousing environments.
- Develop and operate cloud data integration pipelines, event-streaming ingestion, and enterprise orchestration jobs.
- Apply SCD Type 1 and Type 2 patterns, schema evolution, and tiered curation (Bronze/Silver/Gold).
- Support integrations with Oracle ERP and EPM platforms (GL, AP, AR, CM, FA, Projects; FCCS, ARCS,



EDMCS, EPRCS) for finance and operational data needs.
- Internalize the customer context behind each data product and make engineering decisions consistent with it, without requiring the customer in every conversation.
- Choose the fastest responsible path to meet the immediate need, then partner with the team to decide what should become a durable, reusable data product.
- Apply enterprise data standards by default: encryption of sensitive elements, role-based access, audit logging, and retention rules.
- Document data products and contracts clearly in enterprise collaboration tools and the enterprise catalog.
- Own production quality: monitoring, data quality validation, root-cause analysis, and post-deployment support.
- Raise the right questions early, identify owners, and unblock yourself across cross-team dependencies.
- Share patterns, review peer work, and contribute to the team's reusable standards.

What You'll Bring:

- 57 years of data engineering experience delivering production data products at enterprise scale.
- Hands-on experience with contemporary Lakehouse platforms (Delta Lake, Unity Catalog, PySpark, SQL); strong performance tuning and tiered data product design.
- Hands-on experience with cloud data warehousing (SQL, secure views, role-based access, warehouse optimization).
- Strong SQL fundamentals: query optimization,



set-based transformations, reconciliation patterns, SCD Type 1 and Type 2.
- Cloud data integration and orchestration experience (data integration platforms, event streaming, enterprise scheduling tools).
- Working understanding of Power BI and downstream consumption enough to design data products that reporting can actually use.
- Familiarity with Oracle ERP/EPM data flows and integration points (GL, sub-ledger accounting, AP, AR, CM, FA, Projects; FCCS, ARCS, EDMCS, EPRCS).
- Demonstrated ability to operate autonomously on production data products from intent through hypercare without day-to-day direction.
- Customer-minded engineering: builds with the downstream consumer and business outcome in mind; asks the right questions before writing code; uses sound judgment on speed vs. durability.
- Drives clarity in ambiguity surfaces blockers early, names decisions, identifies owners, and proposes a path forward.
- Pragmatic, direct communication clear and concise in writing and standups; able to explain technical decisions to non-engineers.
- Agile delivery experience (Jira, Confluence, CI/CD).

Must Have Skills:

- Azure Data Factory, Azure Databricks, Microsoft Fabric, Delta Lake, SQL, PySpark, Python, DBT(Data Build Tools), Medallion Architecture Real time Streaming Pipelines, Snowflake, Data Modelling, ETL/ELT Pipelines, Control-M, CI/CD, GITLAB

Nice-to-Have:

- Kafka, Azure Event Hub, Deepio
- Familiarity with Agile / Scrum
- AI Tools(Claude, Co-pilot etc.) & AI/ML-ready data preparation
- Familiarity with USGCI, SOX
- Alteryx/ PowerBI
- Background in Finance, Procurement, Network Infrastructure, or Credit Risk data domainsSenior Data Engineer

📌 Sr Engineer, Data (Hyderabad)
🏢 TMUS Global Solutions
📍 Hyderabad