Roles & Responsibilities:
- Design, develop, and implement data pipelines, ETL/ELT processes, and data integration solutions
- Contribute to data pipeline projects from inception to deployment, manage scope, timelines, and risks
- Contribute to 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 cross-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 data-related challenges
- Adhere to best practices 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 documentation of processes, systems, and solutions
What we expect of youWe are all different, yet we all use our unique contributions to serve patients. The [vital attribute] professional we seek is a [type of person] with these qualifications.
Basic Qualifications:
Bachelor s degree with 2 to 6 years of Computer Science, IT or related field experience
Preferred Qualifications:
- 1+ years of experience in designing and supporting biopharma scientific research data analytics (software platforms)
- 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, 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
- Solid understanding of data modeling, data warehousing, and data integration concepts
- Solid experience using RDBMS (e. g. Oracle, MySQL, SQL server, PostgreSQL)
- Knowledge of cloud data platforms (AWS preferred)
- Experience with data visualization tools (e. g. Dash, Plotly, Spotfire)
- Experience with diagramming and collaboration tools such as Miro, Lucidchart or similar tools for process mapping and brainstorming
- Experience writing and maintaining technical documentation in Confluence
- Professional Certifications:Databricks Certified Data Engineer Professional preferred
Soft Skills:
- Strong learning agility, ability to pick up new technologies used to support early drug discovery data analysis needs
- Collaborative with good communication skills.
- High degree of initiative and self-motivation.
- Ability to handle multiple priorities successfully.
- Team-oriented with a focus on achieving team goals.
