The Analytics Engineer designs and develops data pipelines for analysis, collaborates with teams, and creates reports using BI tools.
US Mobile is on a mission to revolutionize connectivity. Imagine a world where you can go into a single app and buy terabytes of data for every one of your devices: phone, smart devices, car, home broadband, and more. That’s the future that US Mobile is building: a software platform built truly for the 21st century and the age of 5G and IoT, with world class engineering, best-in-class user experience, and features that will define the next generation of connectivity.
At the core of it all, we have a team and culture that has been recognized by Forbes as one of the top 500 best startup employers in the US. Our team spans diverse backgrounds, cultures, and stories, with employees coming from 20+ countries.
We’re a venture-backed company entering hypergrowth, having recently ranked 94th on Inc 5000’s fastest-growing private companies in America, and we’re looking for someone exceptional to join our team.
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!
Top Skills
Airflow
BigQuery
Dbt
Looker
Python
Redshift
S3
Snowflake
SQL
Tableau
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