Data Engineer

Job ID 2024-6652

Data Analysis Atlanta, Georgia


Position at WebMD

WebMD Ignite is a full service growth engine for health systems and health-centric organizations. Our comprehensive experience, datasets and breadth of capabilities maximize our partners' marketing investments resulting in an enhanced reputation, deeper loyalty and profitable growth.

Position Summary
The Web Data Engineer is responsible for developing and maintaining a robust data management framework supporting the implementation of our health system client web products. Key responsibilities include building and managing database structures, building and supporting API based data integrations, articulating data nuances to a team of cross functional front end developers, project managers and clients.The ideal candidate will have strong database development and management experience, proficiency in APIs, data migrations and integrations, and a solid understanding and data transformation techniques.


Primary Responsibilities & Essential Functions
Essential Functions:
  • Collaborate with healthcare clients and internal stakeholders to understand data requirements and develop solutions for web data extraction, transformation, and loading.
  • Design and implement robust and scalable data pipelines to collect and integrate web data from healthcare websites, portals, APIs, and other sources.
  • Ensure the accuracy, completeness, and quality of healthcare data collected through web scraping and other techniques, adhering to data governance and compliance requirements.
  • Stay abreast of regulatory changes and industry trends in healthcare data management and privacy (e.g., HIPAA, GDPR) and incorporate best practices into data engineering processes.
  • Monitor data pipeline/integration performance, troubleshoot issues, and optimize processes for efficiency and scalability.
  • Document data pipelines/integrations, processes, and methodologies, and provide support to internal teams and clients as needed.
  • Assist in defining the data management strategy across data domains and products.
  • Oversee data transformation, normalization, cleansing, aggregation, workflow management, and business rule application.
  • Create and maintain documentation to support developed processes and applications.
  • Perform quality assurance checks on data integrity and governance processes.
  • Load, process, and migrate incoming data feeds, as well as create outgoing data extracts.
Minimum Required Knowledge, Skills, Abilities and Qualifications 
  • Bachelor's degree in Computer Science, Information Technology, or related field.
  • Proven experience as a Data Engineer or similar role in product development.
  • SQL competence (query performance tuning) and a grasp of database structure is required.
  • Knowledge of at least one ETL tool (Informatica, SSIS, Talend, Kofax RPA, etc.)
  • Experience with ETL tools, data pipelines, data modeling, and data integration techniques.
  • Knowledge of data quality management, data governance, and performance monitoring.
  • Familiarity with cloud platforms (e.g., AWS, Azure) and related services for data processing and storage.
  • Proficiency in programming languages commonly used in web scraping and data engineering, such as Python, R, or Java,
  • Experience with Drupal 10 is a strong plus
  • Experience with Kofax Kapow Robotic Process Automation (RPA) is a very strong plus
  • Strong attention to detail to ensure accuracy and reliability of data solutions, data integration processes, and data quality management.
  • Effective problem-solving and analytical skills to troubleshoot data issues, optimize data processes, and address challenges during product development and client implementations.
  • Ability to collaborate effectively with cross-functional teams, including project managers, engineers, implementation teams, and clients, to achieve successful outcomes.
  • Customer-centric mindset with a focus on delivering value to clients through effective data solutions, data integration, and technical support during implementations.
  • Commitment to continuous learning and professional development in the field of data engineering, staying updated with industry trends, technologies, and best practices.