Sr. BI Engineer

HighLevel

54d•Remote

About The Position

As a Sr.BI Engineer, you are a detail-oriented problem solver with a passion for turning complex data into actionable insights. You have a deep understanding of data structures, business requirements, and reporting needs, enabling you to design and implement scalable data solutions. Your technical expertise spans data warehousing, pipeline development, and visualization tools, allowing you to empower stakeholders with reliable and efficient data-driven decisions. You thrive in a collaborative environment, take ownership of data governance, and are proactive in identifying opportunities for process automation and optimization. By joining our team, you will play a pivotal role in transforming raw data into meaningful insights, driving business success across the organization.

Requirements

5+ years of experience in business intelligence, data engineering, analytics, or a related field.
Advanced SQL expertise with experience handling complex queries and data transformations.
Strong knowledge of engineering and operations best practices, including version control, data quality assurance, testing, and monitoring.
Data modeling expertise with experience in ETL, Data Warehousing, and Data Lakes.
Data visualization skills using Tableau to create compelling dashboards and reports.
Programming proficiency in one or more languages (e.g., Python, Java) for data processing and analysis.
Basic knowledge of statistical measures and techniques.
Exceptional communication and collaboration skills, with the ability to communicate complex technical information to less technically sophisticated stakeholders and data professionals.

Responsibilities

Own the end-to-end data lifecycle, from ingestion and transformation to delivery, ensuring alignment with business priorities and analytical goals.
Architect and oversee scalable, high-performance data pipelines and warehouse structures that serve as the foundation for company-wide analytics and automation.
Partner with Engineering and Product teams to establish data design standards, naming conventions, and quality benchmarks, ensuring long-term sustainability and performance.
Drive decisions on data architecture, tooling, and storage optimization, balancing scalability, cost, and performance tradeoffs.
Lead data modeling efforts that transform complex, cross-domain data into clear and accessible models supporting business-critical dashboards, experimentation, and AI workloads.
Implement robust data validation frameworks and monitoring systems to proactively detect and resolve data quality issues.
Champion data governance â define standards for access control, lineage, cataloging, and compliance.
Collaborate with security and platform teams to institutionalize best practices for data stewardship and democratized analytics.
Partner with senior business stakeholders to identify high-impact analytical opportunities and translate business questions into scalable data solutions.
Use strong command of SQL, Snowflake, and Python to design complex analytical models and build self-serve dashboards in Tableau or Looker.
Develop and deliver insight frameworks that enable data-informed decision-making across Marketing, Product, and Operations teams.
Mentor analysts and engineers, fostering an environment of learning and technical excellence.
Continuously evaluate and implement emerging data tools and frameworks to enhance speed, accuracy, and reliability of analytics delivery.
Lead initiatives to automate reporting workflows and implement CI/CD for data pipelines, ensuring reproducibility and scalability.
Partner cross-functionally to identify and eliminate data bottlenecks, optimizing for both velocity and reliability in decision support.
Drive a culture of proactive problem-solving through documentation, standardization, and data enablement across teams.