Job Description

Reporting to the Team Lead, Enterprise Data Science and Analytics, the Sr. Enterprise Data Specialist will contribute to evolving a data culture within Bayshore Healthcare through the ongoing initiatives to develop and evolve analytic products within our core analytic suite, Power Insights. They will gain a solid understanding of Bayshore business practices, and the data applications that support these practices, while working in collaboration with other members of the Enterprise Data team, and business resources, to define the organizationxe2x80x99s analytic needs, and then build the analytic solutions that will meet those needs. In this capacity, the Sr. Enterprise Data Specialist will be accountable for analyzing data within source system databases, writing code to extract and transform the data as needed, then guide the Enterprise Architecture and Engineering team in building and testing the dimensional tables and views needed. They will then use these tables and views to create Data Fabric Semantic Models (Datasets) and develop the Power BI reports and dashboards (data visualizations) needed to best fulfill the analytic needs of the business. In addition, the Sr. Enterprise Data Specialist will act as an Enterprise Data xe2x80x9cambassadorxe2x80x9d providing guidance, education, and support to others within the organization in the areas of analytic queries, education on analytic tools, and selection of data visualizations that represent information in the most effective manner. For the near future, the Sr. Enterprise Data Specialist will be engaged almost exclusively on a special xe2x80x9cprovincial phase basedxe2x80x9d project to migrate the Home Care Solutions data to a new source system and will be responsible for working with multiple teams to establish new reporting and analytics based on the new source system and help to transition to these reports as branches are brought online. This project will require travel to branches across Canada depending on which province is being migrated.
Key Responsibilities

• Work with the Business and Support units within Bayshore to define the requirements for key operational reporting metrics and analytic use cases

• Collect, document, profile, and analyze requirements to support the creation of data definitions, business transformation logic, and source to target mapping specifications
• Collaborate with other Enterprise Data team members, including Data Science & Analytics, Data Engineering, and Product Management to design, plan, develop, and deliver data products that best support the organizationxe2x80x99s analytic requirements Design, develop, test, and deploy enterprise-level and division-specific reports, dashboards, and other data products in accordance with defined test scenarios
• Develop detailed data queries to extract data from primary or secondary data sources and build the data stories needed

• Use statistical tools to interpret data sets and work closely with Data Science & Analytics Team Lead and other Data Analysts to build descriptive, prescriptive, diagnostic, and predictive data analytics and models
• Conduct in-depth data analyses, data wrangling, cleaning, and preprocessing to ensure data accuracy, reliability, and quality
• Identify and escalate data and content integrity issues on a timely basis to the Data Management team, and assist in defining Data Quality xe2x80x9ccampaignsxe2x80x9d to address these issues
• Assist with the development and maintenance of data catalog and business glossary to enable ongoing data quality monitoring to ensure consistency in data definitions and build trust in the data across the organization
• Participate in agile ceremonies, with a strong ability to review BRDs and provide concise work breakdown structure and work effort to contribute to monthly release planning
• Adhere to Bayshore Policies and Procedures and maintain confidentiality of client and corporate information
• Complies with all Canadian provincial and federal privacy legislation
• All other duties as required

• Bachelorxe2x80x99s or Masterxe2x80x99s degree in Computer Science, Finance, Data Science, Statistics, Information Systems, or a related field

• Minimum of 5 years of experience as a Data Analyst, with hands-on experience in data handling, manipulation, modeling, and visualization
• Advanced proficiency with Power BI and DAX, with the ability to develop accurate, efficient, and complex SQL queries to extract and integrate data from multiple database sources
• Hands-on experience in Python and familiarity with data analysis libraries, such as Pandas and Numpy
• Demonstrated ability of predictive modeling and techniques ( i.e., regression, classification, clustering etc.)
• Experience working with large and complex datasets with a solid understanding of data lake and warehousing concepts, ETL (Extracts, Transform, Load) development, and data modelling
• Strong analytical skills and ability to collect, organize, analyze and disseminate significant amounts of information with attention to detail and accuracy
• Proficient with Microsoft Office Suite (MS Word, Excel, PowerPoint & Outlook) as well as working knowledge of Microsoft Fabric and Azure Synapse Analytics platforms
• Experience working in an agile environment, with familiarity in agile delivery best practices and tools such as Azure Devops

• Minimum of 5 years of experience as a Data Analyst, with hands-on experience in data handling, manipulation, modeling, and visualization
• Data Analysis experience in a Healthcare environment and familiarity with clinical applications
• Proficiency working with Azure Synapse
• Working experience with other data warehousing solutions such as Snowflake
• Hands-on-experience in MS SQL Server Reporting Services (SSRS), MS SQL Server Integration Services (SSIS), and MS SQL Server Analysis Services (SSAS)

• Excellent interpersonal, communication, and documentation skills, with an aptitude for clear data story telling
• Strong collaborator with the ability to build and sustain effective relationships within the team and with cross-functional stakeholders.
• Self-Drive, with the ability to work independently and take ownership in assigned tasks.
• Continuously enhance knowledge/expertise in own areas and keep current with leading-edge technologies trends.
• Willingness and ability to learn new concepts, processes, and technologies.