Sr Engineer, Data [T500-26982]

Sr. Data Engineer

Finance Intelligence Platform | Data & Reporting Center of Excellence 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.

About the Role:

• T-Mobile's Data & Reporting Center of Excellence (DR COE) is modernizing the data foundation across the entire T-Finance organization. Finance teams manage complex, high-stakes portfolios spanning planning and forecasting, revenue accounting, tax compliance, and treasury operations — all of which are critical inputs to SEC regulatory filings, SOX-controlled close cycles, and executive decision-making.
• Today, many Finance functions still rely on fragmented legacy architectures — proprietary ETL tools, on-premises database servers, aging batch processes, and manually managed spreadsheet models. The DR COE is rebuilding this entire stack on a modern, governed ADLS/Databricks data lakehouse. The Sr. Data Engineer is the hands-on builder at the center of that transformation.
• This role is responsible for designing and delivering the ingestion pipelines, medallion-layer data models, and transformation frameworks that power certified Finance data products. You will be embedded within one or more Finance domain squads based on business priority — contributing to the same shared engineering platform and DR COE standards regardless of domain assignment. Based in Hyderabad, you will collaborate closely with US-based architects, product managers, and Finance domain SMEs across time zones.

What You’ll Do:

• Data Ingestion & Pipeline Engineering: Design and build end-to-end data ingestion pipelines using Azure Data Factory (ADF) from diverse Finance source systems — including ERP platforms, cloud data warehouses, on-premises databases, flat files, and API-based feeds — into the ADLS Bronze layer. Ensure pipelines are monitored, observable, and resilient to upstream schema drift. Apply incremental load patterns and SLA-driven scheduling appropriate to each Finance domain's close cycle and reporting cadence.
• dbt Transformation & Data Modeling: Build and maintain Silver and Gold layer dbt models for Finance data products. Design modular, reusable dbt layers — staging, intermediate, and mart — following DR COE modeling standards. Write comprehensive automated dbt tests covering referential integrity, accepted values, null checks, uniqueness, and domain-specific business rule validations. Maintain dbt documentation and lineage graphs for all published models.
• Legacy ETL Migration: Migrate complex Finance business logic from legacy platforms — proprietary ETL tools, on-premises batch processes, desktop analytics tools, or aging database procedures — into version-controlled, SQL-native dbt models executed on Databricks Workflows. Produce reconciliation evidence confirming 100% output parity between legacy and migrated pipelines before any legacy system is decommissioned.
• Databricks Platform Engineering: Build and maintain Databricks Workflows for pipeline orchestration, auto-scaling compute management, and Delta Lake table optimization. Implement Delta Live Tables (DLT) where streaming or incremental patterns are warranted. Maintain Unity Catalog schemas, table grants, and automated lineage across Bronze, Silver, and Gold layers in alignment with DR COE governance standards.
• Downstream System Integration: Build validated, high-quality data feeds from the ADLS Silver and Gold layers into downstream Finance consumption systems — planning applications, reporting platforms, ERP systems, or regulatory filing pipelines. Ensure published data quality scores — accuracy, lineage, latency, and validation rule pass rates — are maintained for every downstream feed.
• SOX & Compliance Controls: Implement SOX-compliant change management controls across all Finance pipelines: version-controlled dbt models in GitLab with mandatory peer review, CI/CD gates (dev QAT prod), automated regression testing before every promotion, and full ITGC-compliant change audit logs with approver identity and timestamps. Ensure pipelines supporting regulatory or audit-facing outputs include documented lineage and point-in-time reproducibility via Delta Lake time travel.
• Data Quality & Observability: Implement data quality frameworks for assigned Finance pipelines — dbt tests, Databricks data quality monitors, or equivalent checks. Publish and maintain data quality scorecards covering accuracy, completeness, and timeliness. Triage and resolve data quality incidents during time-sensitive close cycles and regulatory filing windows, with clear escalation paths to upstream source system owners.
• Engineering Standards & Collaboration: Partner with US-based Data Architects and Product Managers to translate Finance business requirements into pipeline and data model designs. Participate in sprint ceremonies, contribute to architectural reviews, and uphold DR COE engineering standards across all Finance domain assignments. Mentor junior data engineers on dbt modeling patterns, Databricks best practices, and DR COE platform conventions.

What You’ll Bring:

• 5 to 8+ years of data engineering experience, with at least 3 years in cloud-based data lakehouse environments.
• Strong hands-on experience with Databricks — Delta Lake, Workflows, Unity Catalog, PySpark, and SQL notebooks.
• Solid dbt expertise: modeling patterns (staging intermediate mart), dbt testing frameworks, and CI/CD pipeline integration.
• Proficiency in Python and SQL for pipeline development and data transformation.
• Demonstrated experience building ADF (Azure Data Factory) pipelines for ingestion from relational databases, flat files, and API sources.
• Experience migrating legacy ETL tools (Alteryx, SAS, SSIS, Informatica, or equivalent) to modern, code-first, version-controlled pipelines.
• Familiarity with the Azure ecosystem: ADLS Gen2, Azure DevOps, Azure Key Vault, and Azure Active Directory / Entra ID.
• Experience designing and operating data pipelines in SOX-controlled or compliance-sensitive environments.
• Strong debugging and root-cause analysis skills for complex, multi-hop data pipelines.
• Effective written and verbal communication skills for cross-timezone collaboration with US-based architects and product managers.

Nice to Have:

• Exposure to Finance domain data — any of: ERP systems (Oracle, SAP, Workday), revenue data, planning and forecasting, accounting close cycles, tax compliance, or treasury and securitization datasets.
• Databricks certifications (Data Engineer Associate or Professional).
• Experience with Delta Live Tables (DLT) for streaming or incremental ingestion patterns.
• Familiarity with Oracle ERP or Oracle EBPCS / BPM integration patterns.
• Experience with legacy-to-modern migrations from SAS, IBM TM1, SSAS multidimensional cubes, or on-premises SQL Server.
• GitLab CI/CD pipeline design for data workloads including automated regression test suites.
• Knowledge of T-Mobile DR COE reference architecture, TISS-310 data classification standards, or QSR cybersecurity requirements.
• Prior contribution to SEC regulatory reporting pipelines, SOX ITGC-controlled environments, or audit-ready data lineage design.