Sr. Data Engineer

Would you like to join an international team working to improve the future of healthcare? Do you want to enhance the lives of millions of people? Grifols is a global healthcare company that since 1909 has been working to improve the health and well-being of people around the world. We are leaders in plasma-derived medicines and transfusion medicine and develop, produce and market innovative medicines, solutions and services in more than 110 countries and regions.

Summary:                                                                                                       

The Senior Data Engineer will oversee the business unit’s data integration work, including developing a data model, maintaining a data warehouse and analytics environment, and writing scripts for data integration and analysis. Responsible for designing, developing, and maintaining data pipelines, ensuring data quality, and enabling data-driven decision-making processes.     

Primary responsibilities for role:   

• Independently lead analytical development to extract hidden insights from Real World Medical Data       
• Independently identify insights from data and metadata sources, interpreting and communicating findings to management                                                                         
• Ensure completeness, critical evaluation, correctness and integrity of analyses and datasets                  
• Lead and advise integration of internal and external needs and capabilities of internal RWD team and external vendors; manage vendor process changes that require team to continuously reformat or set up new environments (ie. Snowflake)
• Established, maintains and enforces our data pipeline standards and conventions                               
• Establishes and maintains our data engineering documentation                                                                         
• Manages our data pipeline codebase using external source control repositories as well as within-product tools (e.g., Databricks notebooks)
• Works on significant and unique issues where analysis of situations or data requires an evaluation of intangibles 
• Determines methods and procedures on new assignments                                                        
• Networks with key contacts outside own area of expertise                                                                               
• Exercises judgment in selecting methods, evaluating, adapting of complex techniques and evaluation criteria for obtaining results                                                                          
• Accountable for results, which may impact the entire function                                                                            
• Supervises and manages vendors and external consultant(s)                                                                               
• Serve internally as a subject matter expert; advises others on complex matters                                                                       

Additional Responsibilities:              

• Work closely with teams across biostatistics, data science, data engineering and cloud operations to design and implement data initiatives based on understanding of their use cases                                                               
• Data Governance: Establishes, modifies, and documents data governance projects and recommendations. Implements data governance practices in partnership with business stakeholders and peers. Interprets company and regulatory policies on data
• Provide guidance and hands-on support with real world data management and analysis (real world data can include EHRs, claims, wearables, questionnaires, imaging data, etc.)                                            
• Engage external resources to apply cutting edge methodologies and ensure recognition in the scientific community including publications
• Stay abreast of emerging trends and advancements in data engineering, and software development to continually enhance our research and development operations                                                                                                                                                                 

Knowledge, Skills, and Abilities:     

• Must be a delivery-focused engineer who is passionate about leveraging technology for meaningful and impactful applications
• Ability to rapidly develop and iterate on proofs-of-concept to test new ideas and hypotheses to efficiently validate and evolve software solutions in alignment with strategic Company objectives
• Proficient with data science tools such as R, R data pipelining tools (e.g., Posit connect) and Python lib