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 reliability of the core data pipelines, models, and metrics layer that our dashboards, analyses, and product decisions depend on.
• Work closely with engineering teams to define instrumentation, transform raw and unstructured data into reliable, well-modeled datasets, and ensure that data is trustworthy at scale.
• Partner with business analysts, product managers, and business leaders to translate their reporting and analytical needs into scalable data structures.
• 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.
• 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).

Skills

• Experience with 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)
• Understanding of 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 can translate between technical and business audiences without losing clarity
• Strong sense of ownership and motivation to improve how quickly and reliably the organization can get to trusted data

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
Program-specific awards

Pay

$150K to $180K*

Schedule

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