Data Engineer II leading development and delivery of data pipelines for Syneos Health. Collaborating with teams to optimize data processing and integrate solutions into production environments.
About the role
- AI Engineer responsible for developing and optimizing AI models for data analytics and supply chain at Pfizer. Collaborating with teams to drive innovation and improve patient outcomes.
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.
Requirements
- 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.
- Experience in Python, SQL, and familiarity with Java or Scala.
- Familiarity with Hadoop, Spark, and Kafka for big data processing.
Benefits
- Health insurance
- Flexible working hours
- Professional development opportunities
Job title
Job type
Experience level
Salary
Not specified
Degree requirement
Tech skills
Location requirements
Lead Data Engineer overseeing data operations and analytics engineering teams for OneOncology. Focused on operational excellence in data platform and model reliability for cancer care improvement.
Senior AWS Software Data Engineer at Boeing focusing on AWS Data services to support digital analytics capabilities. Collaborating with cross - functional teams to design, develop, and maintain software data solutions.
Senior Data Engineer designing and improving software for business capabilities at Barclays. Collaborating with teams to build a data and intelligence platform for Equity Derivatives.
Senior AI & Data Engineer developing and implementing AI solutions in collaboration with clients and teams. Working on projects involving generative AI, predictive analytics, and data mastery.
Consultant driving IA business growth in Deloitte's Artificial Intelligence & Data team. Delivering innovative solutions using data analytics and automation technologies.
Data Engineer responsible for managing data architecture and pipelines at Snappi, a neobank. Collaborating with teams to enable data processing and analysis in innovative banking solutions.
Data Engineer at Destinus developing the data platform to support production and analytics needs. Involves migrating Excel sources to Lakehouse and integrating ERP systems in a hybrid role.
Senior Data Engineer developing solutions within the Global Specialty portfolio at an insurance company. Engaging with diverse business partners to ensure high quality data reporting.
Data Engineer at UBDS Group focusing on designing and optimizing modern data platforms. Collaborating in a multidisciplinary team to develop reliable data assets for analytics and operational use cases.