Bridgeway is seeking a Data Engineer (BI) to design, develop, and maintain our data warehouse infrastructure and the semantic models, dashboards, and reporting that sit on top of it. This role involves working closely with analysts, engineers, and business stakeholders to shape our data architecture, build secure and efficient data pipelines and curated data models, and turn data into self-service analytics and insight across the organization. The ideal candidate will have a strong background in data engineering, dimensional and semantic data modeling, business intelligence tooling, and ELT processes, along with a passion for making data accessible and actionable.
This is a remote position with occasional travel. Preference given to East Coast candidates.
Key Responsibilities:
- Design and maintain semantic data models, metrics layers, and certified datasets that provide a consistent, business-friendly source of truth for reporting and self-service analytics.
- Define, standardize, and govern KPIs, calculation logic, and a shared metric glossary so that metrics are consistent and trusted across dashboards and self-service analytics.
- Develop, maintain, and optimize dashboards and reports in Sigma (primary), with some Power BI and native Databricks dashboards/AI-BI Genie , and enable business users to explore data through governed self-service analytics.
- Define and maintain Sigma workspace standards (workbook templates, certified datasets, RLS configuration, naming/governance conventions) in the development instance for promotion across tenant environments, in partnership with Platform Engineering, for tenant-level administration.
- Collaborate with the Architecture team on data quality, testing, and observability; own triage and resolution of BI-layer/dashboard issues.
- Drive BI adoption by training and supporting business users, monitoring dashboard usage, and identifying underused or redundant assets for redesign, training, or deprecation.
- Ensure data security and compliance, including role-based access controls for security, encryption, masking, and governance best practices to ensure compliant handling of sensitive information.
- Gather reporting and analytics requirements from business stakeholders, define success measures, and translate them into technical specifications and well-structured data products.
- Enable analytics, reporting, and AI/ML use cases through well-structured, business-friendly data models, feature availability, and platform integrations using tools such as Databricks Vector Search and Model Serving.
- Collaborate within an Agile-Scrum framework and develop comprehensive technical design documentation to ensure efficient and successful delivery.
- Build and maintain production dashboards and workbooks in Sigma, ensuring reliability and performance for business users.
- Implement row-level security and Entra ID-based access controls to govern and secure data access within the BI/data platform.
- Collaborate and communicate proactively with engineering, analytics, and business stakeholders, influencing priorities and driving alignment across teams.
Requirements:
- 3+ years of hands-on data engineering and/or business intelligence experience required.
- Experience in Databricks, including DAB and Materialized Views.
- 3+ years designing semantic/dimensional data models and building dashboards and reports in a modern BI platform including hands-on experience with a metrics or semantic layer required.
- 3+ years of experience with analytical SQL (ANSI SQL/T-SQL/Spark SQL) and Python for data engineering, including pipeline construction, transformation logic, and automation required.
- Azure DevOps; GitHub CoPilot knowledge is a plus.
- Bachelor’s degree in Computer Science, Information Technology, or a related field. Master’s degree preferred.
- Experience dealing with HIPAA compliant data sets is a plus.
