ROLE SUMMARY

Pfizer's purpose, breakthroughs that change patients' lives, is rooted in being science driven and a patient focused company. Digital and Technology is the driving force of data and AI innovation at Pfizer.

The Data and AI Platforms team, which is part of the Artificial Intelligence Center of Excellence organization is responsible for the creating a seamless experience for engineers to harness data, analytics, machine learning, artificial intelligence, agentic, and visualization capabilities through a unified platform across the enterprise - from research and development, clinical, manufacturing, commercial and enabling functions across all geographies. The team is responsible for the self-service platform ecosystem, developer experience, and exploration of emerging technology.

Part of the Data and AI Platforms team are a group of data engineers who are responsible for enhancing the adoption of unified platform data frameworks, pipeline development practices, and platform across the business You will be responsible for designing, building, and maintaining the scalable data infrastructure, frameworks, and pipelines that power analytics and machine learning initiatives across the organization. This role emphasizes the application of DevOps and DataOps principles, ensuring an agile, automated, and collaborative approach to the entire data lifecycle.

In this role, you will act as the technical engineering lead for data solutions that function as standalone products or reusable platform templates for teams across the enterprise. You will need to balance leading cross-functional teams with hands-on development on the platform and managing stakeholder expectations. You will also be accountable for a team of around 5 colleagues.

You may have a software development background, or an engineering background or you were raised in a modern data analytics culture from the start of your career. You will have the ability to work with technology vendors, support resources, delivery partners, Pfizer stakeholders, and apply emerging and traditional technologies for analytics improvements in support of enterprise analytics platform strategy.

ROLE RESPONSIBILITIES

• Design, construct, install, test, and maintain robust and scalable Extract, Transform, Load (ETL) or Extract, Load, Transform (ELT) data pipelines to pull data from diverse internal and third-party sources.
• Build and manage enterprise data warehouses and data lakes, ensuring optimal performance and data integrity.
• Implement data platforms utilizing cloud services optimizing data delivery architecture to be highly available and fault-tolerant.
• Develop processes for data monitoring and implement data quality checks to ensure the accuracy, completeness, and reliability of core datasets.
• Optimize existing data systems for improved performance and efficiency, implementing automation where possible.
• Partner with data analysts, data scientists, and software engineers to understand and address data needs, ensuring the infrastructure supports analytical goals.
• Create and maintain documentation for all data pipelines, processes, and infrastructure, adhering to best practices in data engineering.
• Drive strategic reuse and user enablement by:
• Developing and maintaining reusable assets for consistency and scalability.
• Defining standards and best practices in partnership with platform owners.
• Assessing and adopting emerging enterprise platform capabilities.
• Delivering end-to-end data solutions to integrate advanced features into business workflows.
• Creating platform specific proof-of-concepts that demonstrate feasibility and readiness for enterprise utilization.
• Ensuring cross-functional alignment for cohesive data and AI adoption across the organization.

BASIC QUALIFICATIONS

• Bachelor's degree in Computer Science, Statistics, or related field.
• At least 10 years of professional experience.
• At least 5 years engineering or technical role experience, ideally involving a complex and rapidly evolving software/product.
• Proven track record of executive level presentations and ability to effectively communicate to multiple audiences and partners.
• Strong leadership skills with experience mentoring and managing development teams.
• Grit when faced with technical issues - you don't rest until you understand what is happening and why things are not working.
• Excellent problem solving and analytical skills with an aptitude for learning new technologies.
• Excellent verbal and written communication skills.
• and the ability to interface with both technical and non-technical individuals as needed.
• Comfort working with and reading code.
• Proven experience as a Data Engineer or similar role with a strongtrack record of delivering production-level data solutions.
• Expertise in Python and proficiency in SQL. Experience with Java or Scala is a plus.
• Strong experience with data warehouse and lake solutions (Snowflake, Redshift, BigQuery, Databricks) and orchestration tools (Apache Airflow, Prefect).
• Big Data Frameworks: Familiarity with big data processing frameworks like Apache Spark or Kafka.
• Solid understanding of data modeling principles, database design, and data governance concepts.
• Hands-on experience and proficiency with DevOps and information tools - e.g., JIRA, Confluence, SharePoint, Yammer, etc.

PREFERRED QUALIFICATIONS

• Experience with cloud platforms such as AWS, Azure, and GCP.
• Experience with data visualization, data science, machine learning, and/or AI
• Experience with web development
• Agile / SAFE Certification

Work Location Assignment: Hybrid

Pfizer is an equal opportunity employer and complies with all applicable equal employment opportunity legislation in each jurisdiction in which it operates.

To apply please visit our website www.pfizercareers.com and search job Director - TL, Data Engineering id 4946109.

Please apply by sending your CV in English.