Sr Engineer, Data - Finance Domain

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Job Overview
Are you ready to join the Un-carrier movement?
This role is essential for designing and developing data architectures across on-premise, cloud, and hybrid platforms to support organizational data needs. It primarily involves collaborating with data engineers to analyze, architect, design, and develop data warehouse and business analytics solutions. The role includes mentoring team members to enhance their data engineering skills and capabilities. Success is measured by the effectiveness of data engineering solutions, team skill development, and contribution to data architecture innovation. The work impacts the organization by enabling data-driven decision-making and advancing data infrastructure capabilities for business insights.

T-Mobile’s Data & Intelligence Center of Excellence supports the modernization of Finance data platforms across planning and forecasting, revenue accounting, tax compliance, treasury operations, and related reporting functions. In this role, you will help build governed, reliable data pipelines and curated Finance data products using a modern Azure Data Lake Storage and Databricks, DBT lakehouse environment. You will work with architects, product managers, Finance domain experts, and engineering partners to migrate legacy processes, improve data quality, and deliver trusted data for analytics, operational reporting, and compliance-sensitive business processes.
We are a team that encourages innovation and advocates an agile and open approach, truly working and playing in the Un-carrier way!

Job Responsibilities:

• Develop data engineering solutions that enable data pipelines, visualization, analytical tools and AI platforms to support business requirements.

• Design and develop data architectures across on-premise, cloud, and hybrid platforms to ensure scalable data infrastructure.

• Build and maintain ingestion pipelines from Finance source systems, including ERP platforms, relational databases, flat files, cloud data warehouses, and API-based feeds, into governed cloud data lake environments.

• Develop and maintain transformation logic and reusable data models using SQL, Python, Databricks, dbt, and related data engineering tools.

• Perform data wrangling, exploration, and discovery of heterogeneous data to generate new business insights.

• Support migration of legacy ETL, batch, and database-driven Finance processes into modern stack.

• Implement data quality checks, validation rules, monitoring, and reconciliation processes to improve accuracy, completeness, lineage, and timeliness of published data.

• Contribute to SOX-sensitive and audit-aware data engineering practices, including peer review, version control, change traceability, testing, and reproducible data processing where applicable.

• Partner with data architects, product managers, Finance domain teams, and engineering peers to translate business requirements into reliable pipeline and data model designs.

• Contribute to team knowledge sharing and drive the advancement of new data engineering capabilities.

• Mentor team members to build and enhance their data engineering skills and professional growth.

• Assist management in product definition, including estimating, planning, and scoping work to meet objectives.

• Also responsible for other duties/projects as assigned by business management as needed.

Education and Work Experience

• Bachelor's Degree plus 5 years of related work experience OR Advanced degree with 3 years of related experience (Required)

• Acceptable areas of study include Computer Engineering, Computer Science, a related subject area (Required)

• 4-7 years Developing cloud solutions using data series; experience with cloud platforms (Amazon Web Services, Azure, or Google Cloud) (Required)

• 4-7 years Hands-on development using and migrating data to cloud platforms (Required)

• Proven track record in SQL, NoSQL, and/or relational database design and development (Required)

• 4-7 years Advanced knowledge and experience in building sophisticated data pipelines with Python, Experience in languages such as SQL, DAX Python, Java, Scala, and/or Go (Required)

Additional Required Qualifications