Analytics Engineer

US Mobile is building the future of wireless communication. The goal: one unified network open to any person and any device, worldwide. Connection without walls.

We’re getting there by empowering customers. All three major networks on one phone and one plan, plus home internet from Starlink. No lock-in. No commitments. Custom fit plans at every price point. 24/7 customer support with real people, empowered to help. We get real-time feedback from Reddit, surveys, and customer support informing product roadmaps and everything we do. It’s working — Consumer Reports named us the top-rated mobile carrier two years in a row.*

And we’re building innovative systems that scale. A network agnostic tech stack. Agile, cross-functional teams built on trust and mutual respect. This work isn’t for everyone. If you work fast, flexibly, and collaboratively — without compromising standards — we want to hear from you.

We are looking for a proactive and detail-driven Analytics Engineer to connect the worlds of data analysis and data engineering. In this role, you will design, develop, and refine data pipelines to transform raw data into meaningful insights that empower marketing, operations, and decision-making teams. If you’re passionate about analytics, automation, and building scalable solutions, we’d love to hear from you.

Job Description

• Work closely with engineering teams to design and develop data structures that enable deeper analysis
• Demonstrate expertise in the analytics engineering development cycle, including data modeling, version control, documentation, testing, and ensuring codebase best practices
• Build visually compelling, high-performance reporting and dashboards using tools like Tableau, Looker, or similar BI platforms to provide valuable insights from large datasets
• Create and optimize data models and schemas to support self-serve analytics and ensure data integrity
• Collaborate with business stakeholders to influence data-driven decision-making, proactively uncovering meaningful patterns and insights
  
  
  

Qualifications

• 4 years of professional experience in analytics engineering, data engineering, or data science
• Strong understanding of data architecture, including building scalable pipelines and optimizing storage solutions for analytical workflows (e.g., S3, Redshift, Snowflake, BigQuery).Strong understanding of data engineering principles, including ETL / ELT processes
• Hands-on experience with data orchestration tools (e.g., Airflow) and data modeling frameworks (e.g., dbt)
• Proficiency in Python or a similar scripting language for data processing and analysis
• Strong expertise in SQL, including experience with data modeling and adherence to database design best practices
• Proven ability to create impactful reports and dashboards using business intelligence tools such as Tableau and Looker
• Experienced in a fast-paced, constantly improving, startup environment that focuses on solving problems with iterative technical solutions
  
  
  

Benefits

• Competitive salary
• Flexible working hours
• Supplemental health insurance
• Professional development stipend
• $500 wfh tech set-up reimbursement
  
  
  

Think you could be a good fit? Apply to learn more!

We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.