Senior Associate, Data Engineer - AI and Automation

ROLE SUMMARY
Pfizer is seeking a highly skilled and motivated AI Engineer to join our advanced technology team. The successful candidate will be responsible for developing, implementing, and optimizing artificial intelligence models and algorithms to drive innovation and efficiency in our Data Analytics and Supply Chain solutions. This role demands a collaborative mindset, a passion for cutting-edge technology, and a commitment to improving patient outcomes.
ROLE RESPONSIBILITIES

• Responsible for data modeling and engineering within the advanced data platforms teams to achieve digital outcomes. Create test plans, test scripts, and perform data validation.

• Conceive, design, and implement Cloud Data Lake, Data Warehouse, Data Marts, and Data APIs.

• Develop complex data products that are beneficial for PGS and Allow for reusability across enterprise.

• Ability to collaborate with contractors to deliver technical enhancements.

• Develop automated systems for building, testing, monitoring, and deploying ETL data pipelines within a continuous integration environment.

• Develop internal APIs and data solutions to enhance application functionality and facilitate connectivity.

• Collaborate with backend engineering teams to analyze data, enhancing its quality and consistency.

• Conduct root cause analysis and address production data issues.

• Design, develop, and implement AI models and algorithms to solve sophisticated data analytics and supply chain initiatives.

• Stay abreast of the latest advancements in AI and machine learning technologies and apply them to Pfizer's projects.

• Provide technical expertise and guidance to team members and stakeholders on AI-related initiatives.

• Document and present findings, methodologies, and project outcomes to various stakeholders.

• Integrate and collaborate with different technical teams across Digital to drive overall implementation and delivery.

• Ability to work with large and complex datasets, including data cleaning, preprocessing, and feature selection

BASIC QUALIFICATIONS

• A bachelor's or master's degree in computer science, Artificial Intelligence, Machine Learning, or a related discipline.

• 3+ years of experience as a Data Engineer, Data Architect, or in Data Warehousing, Data Modeling, and Data Transformations.

• Over 1 years of experience in AI, machine learning, and large language models (LLMs) development and deployment.

• Proven track record of successfully implementing AI solutions in a healthcare or pharmaceutical setting is preferred.

• Strong understanding of data structures, algorithms, and software design principles

• Programming Languages: Experience in Python, SQL, and familiarity with Java or Scala.

• Big Data Technologies: Familiarity with Hadoop, Spark, and Kafka for big data processing.

PREFERRED QUALIFICATIONS

• Data Warehousing: Experience with data warehousing solutions such as Amazon Redshift, Google BigQuery , or Snowflake.

• ETL Tools: Knowledge of ETL tools like Apache NiFi , Talend, or Informatica.

• Cloud Platforms: Hands-on experience with cloud platforms such as AWS, Azure, or Google Cloud Platform (GCP).

• Containerization: Understanding of Docker and Kubernetes for containerization and orchestration.

• AI and Automation: Knowledge of AI-driven tools for data pipeline automation, such as Apache Airflow or Prefect. Ability to use GenAI or Agents to augment data engineering practices

• Data Integration: Skills in integrating data from various sources, including APIs, databases, and external files.

• Data Modeling: Understanding of data modeling and database design principles, including graph technologies like Neo4j or Amazon Neptune.

• Structured Data: Proficiency in handling structured data from relational databases, data warehouses, and spreadsheets.

• Unstructured Data: Experience with unstructured data sources such as text, images, and log files, and tools like Apache Solr or Elasticsearch.

• Data Excellence: Familiarity with data excellence concepts, including data governance, data quality management, and data stewardship.

Please apply by sending your CV and a motivational letter in English.
Work Location Assignment: Hybrid
Purpose
Breakthroughs that change patients' lives... At Pfizer we are a patient centric company, guided by our four values: courage, joy, equity and excellence. Our breakthrough culture lends itself to our dedication to transforming millions of lives.
Digital Transformation Strategy
One bold way we are achieving our purpose is through our company wide digital transformation strategy. We are leading the way in adopting new data, modelling and automated solutions to further digitize and accelerate drug discovery and development with the aim of enhancing health outcomes and the patient experience.
Flexibility
We aim to create a trusting, flexible workplace culture which encourages employees to achieve work life harmony, attracts talent and enables everyone to be their best working self. Let's start the conversation!
Equal Employment Opportunity
We believe that a diverse and inclusive workforce is crucial to building a successful business. As an employer, Pfizer is committed to celebrating this, in all its forms - allowing for us to be as diverse as the patients and communities we serve. Together, we continue to build a culture that encourages, supports and empowers our employees.
Disability Inclusion
Our mission is unleashing the power of all our people and we are proud to be a disability inclusive employer, ensuring equal employment opportunities for all candidates. We encourage you to put your best self forward with the knowledge and trust that we will make any reasonable adjustments to support your application and future career. Your journey with Pfizer starts here!
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