> Markdown version of [/jobs/ext/1301222-sr-business-intelligence-engineer](https://www.wearedevelopers.com/jobs/ext/1301222-sr-business-intelligence-engineer). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Sr. Business Intelligence Engineer - **Company:** NRG BLUEWATER WIND - **Location:** Wawa, PA, United States (Remote available) - **Experience:** Expert - **Salary:** $150,000.0 - $180,000.0 - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Airflow, Information Engineering, Data Infrastructure, Dataspaces, Data Structures, Data Systems, Data Warehousing, Python (Programming Language), Operational Databases, Raw Data, SQL Databases, Unstructured Data, Workflow Management Systems, Core Data, Data Management, Data Pipelines - **Published:** July 16, 2026 - **Apply:** https://careers.nrgenergy.com/talentcommunity/apply/1408721400/?locale=en_US ## About the Role * 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. ## Description 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. The position will start remote and then will move into the hybrid schedule., 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. What You'll Do * You will 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. * You will partner with engineering to define and validate instrumentation and event tracking, ensuring raw data is captured accurately and lands reliably in our data systems. * You will build and optimize data models that turn unstructured and disparate data into clean, reusable datasets that can support reporting and analysis at scale. * You will own data quality end-to-end, including validation, monitoring, and alerting to catch pipeline failures or anomalies before they reach stakeholders. * You will partner with business analysts, product managers, and business leaders to understand their reporting and analytical needs, translating those into scalable, well-structured data models. * You will 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. * You will support self-serve analytics by exposing clean, well-documented datasets and a consistent metrics layer that non-technical stakeholders can rely on. * You will 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. ## Related Videos - [From Messy Queries to Scalable Systems - How Data Engineering actually works](https://www.wearedevelopers.com/videos/100203-from-messy-queries-to-scalable-systems-how-data-engineering-actually-works) - [Data Governance in the Era of AI](https://www.wearedevelopers.com/videos/1622-data-governance-in-the-era-of-ai) - [Enjoying SQL data pipelines with dbt](https://www.wearedevelopers.com/videos/823-enjoying-sql-data-pipelines-with-dbt) - [Data Science in Retail](https://www.wearedevelopers.com/videos/586-data-science-in-retail) - [Bringing Clarity to Event Streams: Enabling Analytics and AI Through Rich Metadata](https://www.wearedevelopers.com/videos/1616-bringing-clarity-to-event-streams-enabling-analytics-and-ai-through-rich-metadata) - [AI Model Management Life Circles: ML Ops For Generative AI Models From Research to Deployment](https://www.wearedevelopers.com/videos/1152-ai-model-management-life-circles-ml-ops-for-generative-ai-models-from-research-to-deployment) ## Related Articles - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [Making Data Warehouses Fast: A Developer’s Story](https://www.wearedevelopers.com/magazine/107-making-data-warehouses-fast-a-developer-s-story) - [Coffee with Developers - Maria Apazoglou - Making AI understandable for all in production](https://www.wearedevelopers.com/magazine/475-coffee-with-developers-maria-apazoglou-making-ai-understandable-for-all-in-production) - [A Guide to Green Tech and Green IT Careers](https://www.wearedevelopers.com/magazine/374-a-guide-to-green-tech-and-green-it-careers) - [Data Engineer Salary UK](https://www.wearedevelopers.com/magazine/253-data-engineer-salary-uk) - [How We Built a Worry-Free System That Runs for 10+ Years – And What We’d Do Again](https://www.wearedevelopers.com/magazine/751-how-we-built-a-worry-free-system-that-runs-for-10-years-and-what-we-d-do-again)