Do you want to make a global impact on patient health? Join Pfizer Digital’s Artificial Intelligence, Data, and Advanced Analytics organization (AIDA) to leverage cutting-edge technology for critical business decisions and enhance customer experiences for colleagues, patients, and physicians. Our team is at the forefront of Pfizer’s transformation into a digitally driven organization, using data science and AI to change patients’ lives. The Data Science Industrialization team is a key driver of Pfizer’s digital transformation, leading engineering efforts to advance AI and data science applications from prototypes and MVPs to full production.
As the AI and Analytics Data Engineering Lead, you will lead a global team responsible for designing, developing, and implementing robust data layers that support data scientists and key advanced analytics/AI/ML business solutions. You will partner with cross-functional data scientists and Digital leaders to ensure efficient and reliable data flow across the organization. Your expertise in data engineering will support our data science community and drive data-centric decision-making.
Join us in making an impact on patient health through the application of cutting-edge technology and collaboration with a diverse team.
Role ResponsibilitiesProvide leadership, supervision, and mentorship for a global team of analytics data engineersLead development of data engineering processes to support data scientists and analytics/AI solutions, ensuring data quality, reliability, and efficiencyEstablish and enforce data engineering best practices, standards, and documentation to ensure consistency and scalability, and facilitate related trainingsPartner with Data Science Industrialization leaders to define team roadmap and provide strategic and technical input on platform evolution, vendor scan, and new capability developmentAct as a subject matter expert for data engineering on cross functional teams in bespoke organizational initiatives by providing thought leadership and execution support for data engineering needsStay updated with the latest advancements in data engineering technologies and tools and evaluate their applicability for improving our data engineering capabilitiesDirect data engineering research to advance design and development capabilitiesCollaborate with stakeholders to understand data requirements and address them with data solutionsPartner with the AIDA Data and Platforms teams to enforce best practices for data engineering and data solutionsCommunicate the value of reusable data components to end-user functions (e.g., Commercial, Research and Development, and Global Supply) and promote innovative, scalable data engineering approaches to accelerate data science and AI workQualificationsMust-HaveBachelor's degree in computer science, information technology, software engineering, or a related field (Data Science, Computer Engineering, Computer Science, Information Systems, Engineering, or a related discipline).10+ years of hands-on experience in working with SQL, Python, object-oriented scripting languages (e.g. Java, C++, etc..) in building data pipelines and processes. Proficiency in SQL programming, including the ability to create and debug stored procedures, functions, and views.2-3 years of hands-on experience leading data engineering, data science, or ML engineering teamsTrack record of managing stakeholder groups and effecting changeRecognized by peers as an expert in data engineering with deep expertise in data modeling, data governance, and data pipeline management principlesExpert knowledge of modern data engineering frameworks and tools such as Snowflake, Redshift, Spark, Airflow, Hadoop, Kafka, and related technologiesExperience working in a cloud-based analytics ecosystem (AWS, Snowflake, etc.)Familiarity with machine learning and AI technologies and their integration with data engineering pipelinesExcellent communication skills to clearly articulate expectations, capabilities, and action plans; actively listen and share information with the team; influence without direct authorityExpertise in leading end-to-end projects by translating business priorities and vision into product/platform thinking, breaking down complex initiatives into action plans, providing functional and technical guidance and SME support, and transitioning to support processesFosters a strong team by sharing responsibility, providing guidance, and developing team members through frequent communication and teamwork.Demonstrated experience interfacing with internal and external teams to develop innovative data solutionsStrong understanding of Software Development Life Cycle (SDLC) and data science development lifecycle (CRISP)Hands on experience working in Agile teams, processes, and practicesAbility to creatively take on new challenges and work outside comfort zone.Strong English communication skills (written & verbal)Nice-to-HaveAdvanced degree in Data Science, Computer Engineering, Computer Science, Information Systems, or a related discipline (preferred, but not required)Experience in solution architecture & designExperience in software/product engineeringExperience with data science enabling technology, such as Dataiku Data Science Studio, AWS SageMaker or other data science platformsFamiliarity with containerization technologies like Docker and orchestration platforms like Kubernetes.Expertise in cloud platforms such as AWS, Azure or GCP.Proficiency in using version control systems like Git.Pharma & Life Science commercial functional knowledgePharma & Life Science commercial data literacyExperience working effectively in a distributed remote team environment.Work Location Assignment: Hybrid
EEO (Equal Employment Opportunity) & Employment Eligibility
Pfizer is committed to equal opportunity in the terms and conditions of employment for all employees and job applicants without regard to race, color, religion, sex, sexual orientation, age, gender identity or gender expression, national origin, or disability.
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