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Data Engineer

Job in Bellevue, King County, Washington, 98009, USA
Listing for: T-Mobile
Full Time position
Listed on 2026-11-05
Job specializations:
  • IT/Tech
    Data Engineering
Salary/Wage Range or Industry Benchmark: 97635 - 176180 USD Yearly USD 97635.00 176180.00 YEAR
Job Description & How to Apply Below
At T-Mobile, we invest in YOU!  Our Total Rewards Package ensures that employees get the same big love we give our customers.  All team members receive a competitive base salary and compensation package - this is Total Rewards. Employees enjoy multiple wealth-building opportunities through our annual stock grant, employee stock purchase plan, 401(k), and access to free, year-round money coaches.

That’s how we’re UNSTOPPABLE for our employees!
** This is not a remote position. T-Mobile is a hybrid work environment requiring work in the office three (3) days per week. The successful candidate will be located in the greater Seattle, Washington area.
** Job Overview As a Data Engineer for the Product Innovation Team, you will play a key role in designing, building, and optimizing scalable data pipelines and cloud-based data architectures that power data-driven products and insights. Working at the intersection of product and engineering, you will collaborate with senior data engineers, technical product managers, data scientists, analysts, and business stakeholders to deliver high-performance data solutions.

In this role, you will build and maintain data pipelines, while supporting modern data lake and data warehouse architectures. You will also help manage data workflows across multi cloud environments such as Snowflake and ADLS.You will write efficient Python and SQL code for data transformation and automation, monitor and optimize pipeline performance, and support data modeling, schema design, and documentation efforts.

The ideal candidate is passionate about scalable data infrastructure and committed to ensuring data quality, security, governance, and privacy compliance across cloud platforms.

Job Responsibilities:

Build and maintain scalable data pipelines using Snowflake and Azure services

Support development of data architectures including data lakes and data warehouses on Azure Integrate and manage data workflows across multi-cloud environments for client solutions.

Monitor, troubleshoot, and optimize data pipelines using system engineering best practices.

Write clean, efficient code in Python and SQL for data transformation and automation

Collaborate with data analysts, scientists, and engineering teams to ensure high-quality, accessible data.

Assist in data modeling, schema design, and documentation of data systems.

Ensure adherence to data security, governance, and compliance standards across cloud platforms

Required

Education:

Bachelors Degree plus 2 years of related work experience OR combination of education and experience deemed equivalent. Acceptable areas of study include Computer Science, Statistics, Informatics, Information Systems or another quantitative field, or equivalent experience

Required

Work Experience:

2-4 years Data Engineering Preferred

Work Experience:

1+ year Exposure to Azure (ADLS and Snowflake1+ years

Experience with big data tools (Spark, Hadoop, etc.
1+ years Experience Familiarity with CI/CD pipelines and Dev Ops practices

Required

Knowledge, Skills and Abilities:

Cloud Computing Collaboration Data Modeling Snowflake (Platform)#LI-Corporate At least 18 years of age Legally authorized to work in the United States Travel:

Travel Required (Yes/No):
No

DOT Regulated:

DOT Regulated Position (Yes/No):
No

Safety Sensitive Position (Yes/No):
No

Total Target Cash Earnings Opportunity: $97,635 - $176,180

National Base Pay Range: $84,900 - $153,200

The Total Target Cash Earnings Opportunity represents the expected total cash compensation for this role at target performance, combining base salary and annual incentive opportunity. Actual earnings may be higher or lower depending on individual performance and overall company results. The base pay range reflects the compensation component…
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