BI & Analytics Analyst/Data Engineer is the key resource for JSSA, and is responsible for all engineering, development, support, and management of data and analytics solutions within the agency.
About the role:We are looking for a driven, analytically sharp BI & Analytics Analyst / Data Engineer to join our growing IT team. This is a hybrid role with an equal split between business intelligence delivery and hands-on data engineering - ideal for someone who loves both telling stories with data and building the infrastructure that powers them.
You will own the end-to-end analytics lifecycle: from shaping SQL Server data warehouse structures to delivering polished, self-service Power BI reports. You will work closely with business stakeholders, 3rd-party data engineers (source data), and IT business partners (and their stakeholders) to turn raw data into reliable, scalable, and actionable insight.
Essential Functions: Business Intelligence & Analytics - Works with IT business partners and operational leaders to design analyses that identify opportunities for improvement in care, evaluates adherence to clinical best practice, and measures outcomes.
- Assists with ensuring that agency data repositories produce consistent, reusable data through collaboration with key staff to develop, implement and provide guidance on standards and best practices.
- Promotes best-practice knowledge and use to business stakeholders enabling self-service analysis vs. IT owned development.
- Own self-service reporting datasets, including DAX measures, data models, and row-level security.
- Translate business requirements into clear analytical deliverables, manage stakeholder expectations and iterate based on feedback.
- Monitor report usage and data quality, proactively identifying and resolving issues.
- Document data definitions, metric logic, and report lineage to support a data-literate culture within the agency.
- Uses technical tools to query, manipulate, and summarize data from various data sources.
- Assists in designing, developing, maintaining, and updating databases on department and organizational needs.
Data Engineering - Design and build star schema data warehouse objects in SQL Server, including fact tables, dimension tables, and aggregate layers.
- Write and maintain T-SQL stored procedures, ETL pipelines, and staging-to-DWH data loads.
- Develop and own source-to-target mapping documentation for new data domains.
- Integrate data from source systems.
- Contribute to data quality, pipeline reliability, and warehouse performance optimization
- Support the adoption of self-service analytics by building clean, well-documented datasets.
- Document current data architecture, define logical/physical data and establish agency data blueprint.
- Management and support of data warehouse solution (Wherescape RED), SQL Server and associated te
Data Management - Define operational monitoring and alerting tools to ensure end to end delivery of trusted, quality data from source systems to consumption.
- Establish best practice standards and processes for data automation, orchestration, and transformation.
- Identify, design, implement and manage master data management solution for client and employee subjects. Work with key stakeholders to define data quality standards and operational DQ processes.
Minimum Education, Licensure, and Work Experience Required: - Bachelor's degree required; Master's degree highly preferred
- 5-7+ years of experience in a BI, analytics, or data engineering role
- Strong proficiency in SQL Server and T-SQL - including stored procedures, window functions, and query optimization
- Hands-on experience building and maintaining Power BI reports and semantic models (DAX, Power Query)
- Hands-on experience with Wherescape OLAP solution. Experience with alternative OLAP solutions (e.g., Azure Analysis Service, Azure Data Lake, and Azure Synapse Analytics).
- Experience integrating or working with EHR data (reports, APIs, or data exports)
- Familiarity with star schema / dimensional modelling concepts (Kimball methodology a plus)
- Python experience for data wrangling, automation, or pipeline scripting
- Experience with Microsoft Master Data Services (MDS), including defining entities, and creation of business rules.
- Experience with Microsoft Data Quality Services (DQS) and SQL Server Integration Services (SSIS).
- Comfortable working across the full analytics stack - from raw source data to end-user report.
- Strong communication skills - able to explain data concepts clearly to non-technical stakeholders.
- Advanced skill set with Microsoft office suite (Power BI), SQL, and experience with EMR systems (hospice, homecare, and/or mental health) desired.
