Sr Data Engineer - Biological Studies

In this vital role, you will design, build, and maintain data lake solutions for scientific data that drive business decisions for Research. You will build scalable and high-performance data engineering solutions for large scientific datasets and collaborate with Research customers. Responsibilities Design, develop, and implement data pipelines, ETL/ELT processes, and data integration solutions. Take ownership of data pipeline projects from inception to deployment, including scope, timelines, and risks. Develop and maintain data models for biopharma scientific data, data dictionaries, and other documentation to ensure data accuracy and consistency. Optimize large datasets for query performance. Collaborate with global multi-functional teams, including research scientists, to understand data requirements and design solutions that meet business needs. Implement data security and privacy measures to protect sensitive data. Leverage cloud platforms (AWS preferred) to build scalable and efficient data solutions. Collaborate with Data Architects, Business SMEs, Software Engineers, and Data Scientists to design and develop end-to-end data pipelines to meet fast-paced business needs across geographic regions. Identify and resolve complex data-related challenges. Adhere to standard methodologies for coding, testing, and designing reusable code/component. Explore new tools and technologies that will help to improve ETL platform performance. Participate in sprint planning meetings and provide estimations on technical implementation. Maintain comprehensive documentation of processes, systems, and solutions. Basic Qualifications Master's degree with 4 - 6 years of experience in Computer Science, IT, Computational Chemistry, Computational Biology/Bioinformatics, or related field. OR Bachelor's degree with 6 - 8 years of experience in Computer Science, IT, Computational Chemistry, Computational Biology/Bioinformatics, or related field. OR Diploma with 10 - 12 years of experience in Computer Science, IT, Computational Chemistry, Computational Biology/Bioinformatics, or related field. Preferred Qualifications 3+ years of experience in designing and supporting biopharma scientific research data pipelines. Must-Have Skills Proficiency in SQL and Python for data engineering, test automation frameworks (pytest), and scripting tasks. Hands-on experience with big data technologies and platforms, such as Databricks, Apache Spark (PySpark, SparkSQL), workflow orchestration, and performance tuning on big data processing. Excellent problem-solving skills and the ability to work with large, complex datasets. Good-to-Have Skills A passion for tackling complex challenges in drug discovery with technology and data. Experience writing and maintaining technical documentation in Confluence. Professional Certifications Databricks Certified Data Engineer Professional (preferred).