Sr. Business Intelligence Engineer

About the role

Vivint Smart Home is hiring a Senior Business Intelligence Engineer to join the central analytics team within our product organization. This role is responsible for building and maintaining the data infrastructure that powers how the product organization measures, understands, and improves its business.

Responsibilities

• Own the design, development, and maintenance of the core data pipelines and warehouse models that power reporting and analytics across the product organization, ensuring data is reliable, well documented, and consistently used.
• Partner with engineering teams on instrumentation, schema design, and data capture, ensuring raw data is captured accurately and lands reliably in our data systems.
• Build and optimize data models that turn unstructured and disparate data into clean, reusable datasets that can support reporting and analysis at scale.
• Own data quality end-to-end, including validation, monitoring, and alerting to catch pipeline failures or anomalies before they reach stakeholders.
• Partner with business analysts, product managers, and business leaders to understand their reporting and analytical needs, translating those into scalable, well-structured data models.
• Build and maintain internal tools and automation, including the use of AI and scripting, to reduce manual reporting effort and improve how quickly the organization can get to trusted data.
• Support self-serve analytics by exposing clean, well-documented datasets and a consistent metrics layer that non-technical stakeholders can rely on.
• Contribute to the evolution of our analytics platform, including our data warehouse, orchestration, and tooling, improving how data is built, scaled, and maintained over time.

Requirements

You have experience in a data engineering, analytics engineering, or business intelligence role where you were responsible for building and owning production data pipelines. You are fluent in SQL and Python and comfortable building and maintaining data pipelines. Experience with orchestration tools (such as Airflow) and transformation frameworks (such as dbt) is expected. You understand data modeling and warehousing best practices, and can design data structures that are reusable, well documented, and built to scale. You have experience partnering with engineering teams on instrumentation, schema design, and data capture, and can work effectively across technical systems. You are highly analytical and able to take an ambiguous data problem and turn it into a scalable, production-ready solution. You are comfortable working across teams and can translate between technical and business audiences without losing clarity. You have a strong sense of ownership and are motivated to improve how quickly and reliably the organization can get to trusted data, including through the use of emerging tools and AI.

Qualifications

You have a Bachelor’s degree in Computer Science, Data Science, Statistics, Engineering, or a related field. You have 5+ years of relevant experience in data engineering, analytics engineering, or business intelligence. You are proficient in SQL and Python and have experience with orchestration tools (such as Airflow) and transformation frameworks (such as dbt). You have experience designing and optimizing data models, and you are skilled in data quality management. You have experience working with business analysts, product managers, and business leaders to translate their reporting and analytical needs into scalable data models. You are comfortable working in ambiguity and can independently drive a data solution from problem definition through production. You have a strong sense of ownership and are motivated to improve how quickly and reliably the organization can get to trusted data, including through the use of emerging tools and AI.

Skills

• Experience in data engineering, analytics engineering, or business intelligence
• Fluency in SQL and Python
• Experience with orchestration tools (such as Airflow) and transformation frameworks (such as dbt)
• Data modeling and warehousing best practices
• Experience partnering with engineering teams on instrumentation, schema design, and data capture
• Highly analytical and able to take an ambiguous data problem and turn it into a scalable, production-ready solution
• Comfortable working across teams and translating between technical and business audiences
• Strong sense of ownership and motivation to improve how quickly and reliably the organization can get to trusted data
• Experience with emerging tools and AI

Benefits

• Free daily lunch and drinks on site
• Paid holidays and flexible paid time away
• Employee/Friends/Family Discounts
• Onsite health clinic, gym, gaming tables
• Medical/dental/vision/life coverage & 24/7 Medical Hotline
• 401(k) + Employer Match

Pay

The base salary range for this position is $150K to $180K. The range listed is just one component of the total compensation package for employees. Other rewards may include annual bonus, short- and long-term incentives, and program-specific awards. In addition, the position may be eligible to participate in the benefits program which includes, but are not limited to, medical, vision, dental, 401K, and flexible spending accounts.

Schedule

The position will start remote and then will move into the hybrid schedule. The position requires an in-office presence in Seattle, WA on a hybrid schedule for Monday, Tuesday, Wednesday, and Thursday with a work from home day on Friday.