Data Engineer

• Designs and develops data pipelines that extract data from various sources, transforms it into the desired format, and loads it into the appropriate data storage systems using CI/CD tools and practices
• Integrates data from different sources, including databases, data warehouses, APIs, and external systems
• Creates robust data models and architectures to support analytics initiatives
• Collaborates with business stakeholders to understand their analytics needs and delivers comprehensive reports, dashboards, and models
• Collaborates with data analysts to optimize models and algorithms for data quality, security, and governance
• Ensures data consistency and integrity during the integration process, performing data validation and cleaning as needed
• Ensures all data engineering activities comply with HIPAA and other relevant healthcare data privacy regulations
• 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
• Establishes the governance of data and algorithms used for analysis, analytical applications, and automated decision making
• Fosters the creation of a data-driven culture, related competencies, and data literacy across the enterprise
• Defines delivery models, methods and practices for creation of data products to ensure consistent application and use of data and analytics solutions
• Assists in the development, tracking, and reporting of organizational key performance indicators (KPIs) and additional data to support strategic planning and the annual planning and budgeting process
• Deliver on agreed-upon impact metrics, including pipeline reliability, data quality improvements, and stakeholder satisfaction
• Pursues ongoing learning opportunities and certifications (e.g. AWS Certified Data Analytics, Azure Data Engineer Associate)

• A bachelor’s or master’s degree in computer science, data science, software engineering, information systems, or related quantitative field
• At least two 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
• Ability to design, build, and deploy data solutions that capture, explore, transform, and utilize data to support AI, ML, and BI tools
• Strong ability in programming languages such as Python, Java, and C/C++ with experience writing production code
• 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, Microsoft Fabric)
• Experience with database technologies such as SQL, 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
• Ability to communicate complex technical concepts to non-technical stakeholders
• 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
• Familiarity with working with Medicare and other health-related data sets preferred
• Experience with data analysis tools like SQL, Excel and statistical software

Familiarity with working with Medicare and other health-related data sets preferred

• Health Insurance
• Dental Insurance
• Vision Insurance
• Retirement with Company Match
• Paid Time Off
• Paid Volunteer Time
• Thrift Shop Discount