Why Patients Need You

Pfizer’s purpose, breakthroughs that change patients’ lives, is rooted in being a science driven and a patient focused company. Digital, AI, data, and analytics are central to driving innovation at Pfizer.

What You Will Achieve

Senior Manager, Solution Engineer will be on a team responsible for the execution of the technical strategies and development of the digital solutions to support our colleagues across Finance, People Experience, Legal, Compliance, and other Enabling Functions.

This position will lead the design, development, and maintenance of our data infrastructure and data products with a strong emphasis on data quality, data modeling. Senior Manager, Solution Engineer will be part of an agile team working closely with Product Owner on developing the roadmap for technical products and a collaborator in a larger cross functional environment of technical experts from various digital organization at Pfizer.

How You Will Achieve It

• Lead the design, development, and maintenance of scalable data pipelines and ETL processes.
• Collaborate with data scientists, analysts, and other stakeholders to understand data requirements and deliver solutions.
• Map business needs to enterprise architecture standards and reusable assets to ensure time/quality/cost benefits.
• Implement and oversee data quality checks and monitoring to ensure data accuracy and reliability.
• Optimize data storage and retrieval processes to improve performance and efficiency.
• Work with cloud-based data platforms and tools to manage and process large datasets.
• Ensure data security and compliance with relevant regulations and standards.
• Troubleshoot and resolve complex data-related issues and provide support to end-users.
• Lead, mentor and guide junior data engineers.
• Identify, evaluate and leverage emerging and innovative approaches, frameworks and technologies where applicable.
• Collaborate with key stakeholders across Enabling Functions and Client Partner organizations.
• Create and maintain technical documentation. 

Qualifications

Must-Have

• Bachelor's degree in Computer Science, Engineering, or a related field.
• At least 7 years of experience as a Data Engineer or in a similar role.
• Strong knowledge of SQL and experience with relational and non-relational databases, preferably Snowflake or other (Redshift, PostgreSQL).
• Experience with different types of ingestions (stream, batch, APIs).
• Proficiency in programming languages such as Python or Java, R, Scala.
• Extensive experience with cloud platforms such as AWS, Azure, or Google Cloud.
• Strong understanding of microservices architecture and container services.
• Working experience with cloud platforms such as AWS, Azure, or Google Cloud.
• Working experience with DevSecOps practices such as CI/CD and automated testing to ensure the reliability and scalability of data pipelines.
• In-depth knowledge of big data technologies such as Spark, Hadoop.
• In-depth knowledge of data orchestrators such as Airflow.
• In-depth knowledge of data transformation tools such as dbt.
• Experience with applying DataOps principles to improve the efficiency and quality of data workflows, including version control, monitoring, and collaboration.
• Good understanding of data quality and data modeling.
• Experience with data governance and data management best practices (Alation, Collibra or similar).
• Strong communication and collaboration skills.

Nice-to-Have

• Working experience with different types of data formats.
• Working experience with open source data engineering tools.
• Experience with data visualization tools such as Tableau or Power BI.
• Knowledge of machine learning and data science concepts.

  
  Work Location Assignment: Hybrid

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