Sr Engineer, Data - Finance Domain

T-Mobile

Quick summary

Work type
On-site
Location
Frisco, TXBellevue, WA
Salary
$105,100–$189,600 / yr
Posted
1 day ago

Market check

Salary context

Below market

How this pay compares to similar roles

Similar $172k
This role $147k
$93k most similar roles pay here $215k

This role pays less than 72% of similar roles. Most pay $139,500–$203,650 — the shaded band above. At the midpoint, this role pays about $147k versus about $172k for comparable roles.

Based on 240 similar postings.

Employer

About T-Mobile

T-Mobile US is the second-largest wireless carrier in the United States, providing wireless voice, messaging, and data services under the T-Mobile and Metro by T-Mobile brands. Industry: Wireless Telecommunications

T-Mobile currently has 32 open roles on FindRole.

Listed pay typically runs $113,600–$186,400 across 31 roles with salary data.

Most-posted roles

View all roles at T-Mobile

At a glance

TL;DR · Sr Engineer, Data - Finance Domain

As a Senior Data Engineer at T-Mobile’s Data & Intelligence Center of Excellence, you will collaborate with data engineers and domain experts to design and develop modern Azure-based data architectures. Your daily tasks include building governed data pipelines and curated Finance data products using Databricks and DBT in a lakehouse environment. You’ll work closely with architects, product managers, and engineering teams to migrate legacy processes, enhance data quality, and ensure compliance for SOX-sensitive operations. Key skills required are 4-7 years of experience in cloud platforms like Azure, proficiency in SQL, Python, Databricks, dbt, and a strong background in data modeling and transformation logic. This role supports Finance functions such as planning, revenue accounting, and treasury operations, aiming to enable data-driven decision-making across the organization.

What you'll do

  • Design and develop data architectures across various platforms to ensure scalable infrastructure.
  • Build ingestion pipelines from Finance source systems into governed cloud data lake environments.
  • Develop transformation logic and reusable data models using SQL, Python, Databricks, and dbt.
  • Implement data quality checks and validation rules for business-critical data pipelines.
  • Mentor team members to enhance their data engineering skills and capabilities.
  • Support migration of legacy ETL processes into modern cloud-based solutions.

What we're looking for

  • 4-7 years of experience developing cloud solutions with AWS, Azure, or Google Cloud.
  • Proven track record in SQL and Python for data engineering tasks.
  • Hands-on experience building and maintaining complex data pipelines in cloud environments.
  • Advanced knowledge in Databricks, dbt framework, and related data engineering technologies.
  • Ability to collaborate effectively with architects, product managers, and business partners.
  • Experience implementing data quality controls and monitoring processes.
  • Familiarity with version control systems and CI/CD practices.

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