Stream Realty Partners needs to advance its enterprise analytics strategy by designing and implementing scalable, Azure-based data solutions to modernize its data warehouse environment, ensuring speed, accuracy, and scalability to support rapid growth and enable leadership to evaluate datasets across multiple departments.
Requirements
- Proven experience with Azure Fabric and the broader Microsoft Azure data ecosystem.
- Strong background in data warehousing (design, build, support) and ETL/ELT development.
- Expertise with SQL Server, Azure Synapse, Data Lake, Data Factory, Power BI.
- Solid understanding of dimensional data modeling and BI best practices.
- Experience enabling self-service BI environments and mentoring end users.
- Project management experience (Agile/Scrum and/or Waterfall).
- Azure, TOGAF, or Agile/Scrum certifications are highly valued.
Responsibilities
- Develop long-term data warehouse strategies aligned with business goals, emphasizing Azure Fabric and cloud-first approaches.
- Define enterprise data standards, models, and architectures to support robust BI adoption.
- Recommend and implement modern Azure data solutions (Azure Fabric, Synapse, Data Lake, Data Factory, Databricks, Snowflake, etc.).
- Select and configure optimal ETL/ELT tools to ensure seamless integration of enterprise data sources.
- Design and maintain efficient data pipelines and models to support Power BI and enterprise reporting.
- Proactively monitor, troubleshoot, and optimize warehouse performance.
- Collaborate with stakeholders to deliver dashboards, KPIs, and BI reports that drive actionable insights.
Other
- Drive automation, scalability, and self-service capabilities to support Stream’s growth.
- Continuously evaluate emerging Azure services for innovation opportunities.
- Ensure data integrity, security, and compliance across all environments.
- Act as a trusted advisor and mentor for business stakeholders, analysts, and technical staff.
- Deliver training sessions and workshops on Power BI, self-service analytics, and data best practices.
