Senior Associate, Data Engineer – AI and Automation
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Job Location:
Thessaloníki - Greece
Monthly Salary:
Not Disclosed
Posted on:
30+ days ago
Vacancies:
1 Vacancy
Job Summary
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 Pfizers 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 bachelors or masters 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 apatient 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 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 iscommitted to celebratingthisin all itsforms 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!
Required Experience:
Senior IC
Key Skills
- Continuous Integration
- APIs
- Jenkins
- Junit
- Distributed Control Systems
- Testng
- GAMP
- Test Automation
- CI/CD
- Cucumber
- Programmable Logic Controllers
- Selenium
About Company
Erfahren Sie mehr über uns als forschendes und produzierendes Pharmaunternehmen: Von unserem Beitrag zum medizinischen Fortschritt bis zur nachhaltigen Produktion.
