Bachelor's degree in computer science, data science, software engineering, information systems, or a related field; master's degree preferred.
Six years of experience in data management disciplines and direct responsibility for data engineering tasks.
Proven track record in developing and maintaining data warehouses, particularly with big data solutions.
Experience in programming languages like SQL, Python, and R for data analysis and manipulation.
At least five years of healthcare industry experience.
Responsibilities
Design and develop data pipelines for data extraction, transformation, and loading.
Collaborate with data analysts to optimize data models focused on quality and governance.
Integrate diverse data sources, including databases, APIs, and external systems.
Ensure data consistency and integrity through validation and cleaning processes.
Transform raw data using cleansing, aggregation, and enrichment techniques.
Optimize performance and scalability of data processing workflows and pipelines.
Implement data quality checks within pipelines to ensure accuracy and completeness.
Benefits
Opportunity for leadership and supervisory role within the Data Analytics team.
Engagement with hospital executives to shape data management as a core business asset.
Involvement in modern data architecture using cloud services and advanced analytics.
Development and optimization of reporting tools for all hospital business units.
Focus on innovative data integration techniques that enhance decision-making capabilities.
Full Job Description
JOB DESCRIPTION DETAILS
Job Summary:
Description: The Data Analytics Lead is responsible for designing, developing, and maintaining the infrastructure and systems required for data storage, processing, and analysis. They play a crucial role in building and managing the data pipelines that enable efficient and reliable data integration, transformation, and delivery for all data users across the enterprise. They supervise the Data Analytics team and help to build reporting and systems to provide hospital leadership with accurate and timely reporting. Responsibilities
Designs and develops data pipelines that extract data from various sources, transform it into the desired format, and load it into the appropriate data storage systems.
Collaborates with and manages data analysts to optimize models and algorithms for data quality, security, and governance.
Integrates data from different sources, including databases, data warehouses, APIs, and external systems.
Ensures data consistency and integrity during the integration process, performing data validation and cleaning as needed.
Transforms raw data into a usable format by applying data cleansing, aggregation, filtering, and enrichment techniques.
Optimizes data pipelines and data processing workflows for performance, scalability, and efficiency.
Monitors and tunes data systems, identifies and resolves performance bottlenecks, and implements caching and indexing strategies to enhance query performance.
Implements data quality checks and validations within data pipelines to ensure the accuracy, consistency, and completeness of data.
Takes authority, responsibility, and accountability for exploiting the value of enterprise information assets and of the analytics used to render insights for decision making, automated decisions and augmentation of human performance.
Works with executives to establish the vision for managing data as a business asset.
Establishes the governance of data and algorithms used for analysis, analytical applications, and automated decision making.
Builds reports for all business units of the hospital and maintains reports and dashboards to ensure information is accurate and up to date.
Builds program for and manages Data Governance efforts.
Education:
A bachelor's degree in computer science, data science, software engineering, information systems, or related quantitative field; master's degree preferred.
Registration/Certification/Licensure:
Experience:
At least six years of work experience in data management disciplines, including data integration, modeling, optimization and data quality, or other areas directly relevant to data engineering responsibilities and tasks.
Proven project experience developing and maintaining data warehouses in big data solutions.
Experience with programming languages such as SQL, Python, and R for data manipulation and analysis Preferred.
Project experience with data analysis and visualization tools like Tableau, Power BI, Excel, or others.
At least 5 years in Healthcare work experience
Other Requirements:
Maintains unit-specific and hospital competencies, mandatory learning, and any clinical certifications required in accordance with the Staff Education and Training policy GA-057 and/or any other department requirements.
Ability to design, build, and deploy data solutions that capture, explore, transform, and utilize data to support AI, ML, and BI.
Ability in data science languages/tools such as SQL, R, SAS, or Excel.
Proficiency in the design and implementation of modern data architectures and concepts such as cloud services (AWS, Azure, GCP) and modern data warehouse tools (Snowflake, Databricks).
Experience with database technologies such as SQL, NoSQL, Oracle, Hadoop, or Teradata.
Ability to collaborate within and across teams of different technical knowledge to support delivery and educate end users on data products.
Expert problem-solving skills, including debugging skills, allowing the determination of sources of issues in unfamiliar code or systems, and the ability to recognize and solve repetitive problems.
Excellent business acumen and interpersonal skills; able to work across business lines at a senior level to influence and effect change to achieve common goals.
Ability to describe business use cases/outcomes, data sources and management concepts, and analytical approaches/options.
Ability to communicate between executives, business, IT, and other stakeholders.
