Principal Data Engineer

Reporting to Senior Director of Data and Analytics as Principal Data Engineer, you will be responsible for leading the design, development, and implementation of our data infrastructure. Leveraging your deep technical expertise and leadership skills, you will play a critical role in shaping our data platform strategy, architecture, and capabilities to unlock actionable insights and deliver value across the organization. You will work closely with cross-functional teams to ensure our data systems are scalable, secure, and optimized for performance. Your expertise in Microsoft Azure data platforms, combined with your data science and software engineering skills, will be crucial in driving our data strategy forward.
Position Responsibilities: 

• Lead the design and architecture of scalable, reliable, and secure data infrastructure using Microsoft Azure data platforms (Azure Data Lake, Azure SQL Database, Azure Synapse Analytics, etc.).
• Develop, implement, and optimize data pipelines for ETL processes, ensuring data is accurately and efficiently processed and stored.
• Collaborate with data scientists, analysts, and software engineers to understand data needs and develop data products that support business objectives.
• Implement data integration solutions to consolidate data from various sources into a unified data platform.
• Monitor and troubleshoot data pipelines to ensure reliable and timely data delivery.
• Develop and maintain documentation for data pipelines, data models, and data workflows.
• Work with DevOps teams to automate deployment and monitoring of data solutions.
• Support data science initiatives by providing clean, structured data and building pipelines for machine learning models.
• Utilize data science techniques to analyze large datasets and provide actionable insights.
• Stay up to date with the latest industry trends and technologies, ensuring our data infrastructure remains at the forefront of innovation.
• Collaborate with stakeholders to define data requirements and develop strategies for data acquisition, storage, and retrieval.

Qualifications and Skills Required:

• Bachelor’s or master’s degree in computer science, Data Science, Engineering, or a related field.
• 8+ years of experience in data engineering, with a strong background in data science and software engineering in pharmaceutical industry preferred.
• 6+ years’ experience with Microsoft Azure data platforms (Azure Data Lake, Azure SQL Database, Azure Synapse Analytics, Azure Databricks, etc.).
• Proficient in programming languages such as Python, Java, or Scala.
• 6+ years of experience in data modeling, modern data pipeline, ETL processes, and creating data products.
• Proficiency in using Azure Machine Learning for model training and deployment
• Knowledge of machine learning techniques and frameworks.
• Excellent problem-solving skills and the ability to work in a fast-paced, dynamic environment.
• Strong communication and collaboration skills, with the ability to work effectively with cross-functional teams.
• Experience with DevOps practices and tools for CI/CD in data engineering projects is a plus.

Compensation:
Base salary is determined by several factors that include, but are not limited to, a successful candidate's qualifications, skills, education, experience, business needs, and market demands. The role may also be eligible for bonus, equity, and comprehensive benefits, which include flexible paid time off (PTO), medical, dental, vision, and life and disability insurance.