Sr. Business Intelligence Engineer

NRG•VIRTUAL, WA

10d•$150,000 - $180,000•Hybrid

About The Position

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 our business. You will own the design, development, and reliability of the core data pipelines, models, and metrics layer that our dashboards, analyses, and product decisions depend on. This role sits at the center of the product, engineering, and data ecosystem. You will 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. You will also partner with analysts, product managers, and business leaders to translate their reporting and analytical needs into scalable data structures. This is a role for someone who is comfortable working in ambiguity, can independently drive a data solution from problem definition through production, and takes ownership for the quality and reliability of their work.

Requirements

Experience in a data engineering, analytics engineering, or business intelligence role where you were responsible for building and owning production data pipelines.
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.
Understand data modeling and warehousing best practices, and can design data structures that are reusable, well documented, and built to scale.
Experience partnering with engineering teams on instrumentation, schema design, and data capture, and can work effectively across technical systems.
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 motivated to improve how quickly and reliably the organization can get to trusted data, including through the use of emerging tools and AI.

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 to define and validate instrumentation and event tracking, 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.