Sr. Data Engineer

Job Description:

We are seeking an experienced and highly skilled Cloud Data Engineer to join our team in the pharmaceutical industry. The successful candidate will have a strong background in data engineering, with expertise in data ingestion, ETL, analytics, and other data-related services, specifically using AWS Services like Glue, Kinesis, etc. In this role, you will play a critical part in developing and implementing data-driven solutions for our organization, ensuring adherence to cybersecurity and data privacy regulations. This position is based in South San Francisco and offers a hybrid working model.

Responsibilities:

• Design, develop, and maintain data pipelines using AWS services, such as S3, EMR, Redshift, Glue, Athena, Sagemaker, DynamoDB, and Kinesis streams.
• Ensure data privacy, security, and governance principles are integrated into all data engineering tasks.
• Collaborate with cross-functional teams to define data integration requirements and develop data-driven solutions.
• Leverage your 5-7 years of hands-on experience in data engineering, focusing on data ingestion, ETL, analytics, and AWS Glue and Kinesis streams, Quicksight and Data Analytics.
• Work closely with data architects and scientists to optimize feature engineering and data manipulation processes.
• Develop complex, high-quality solutions to address pharmaceutical industry-specific data challenges.
• Provide examples of complex projects you have successfully completed and the impact of your work.
• Stay current with industry best practices and emerging trends in data engineering and cloud technologies.

Qualifications:

• Bachelor's degree in Computer Science, Engineering, or a related field.
• Minimum 5-7 years of hands-on experience in data engineering, with a strong focus on cloud-based solutions.
• Expertise in AWS cloud services related to data storage, integration, and processing, including AWS Glue and Kinesis streams.
• Proficiency in Python and other programming languages for building data pipelines.
• Experience with PySpark and related data processing frameworks.
• Strong understanding of data privacy and security principles, with specific focus on the pharmaceutical industry.
• Excellent communication skills, including the ability to present technical information in a clear and concise manner.
• Ability to work collaboratively within a team and contribute to complex projects.
• Experience with Airflow for job orchestration, MLOps, Snowflake is a plus
• AWS certifications (e.g., AWS Certified Data Analytics, AWS Certified Solutions Architect) are highly desirable.