- 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 you
We are all different, yet we all use our unique contributions to serve patients.
Basic Qualifications:
Bachelor's degree and 0 to 3 years of Computer Science, IT or related field experience OR
Diploma and 4 to 7 years of Computer Science, IT or related field experience
Preferred Qualifications:
1+ years of experience in implementing and supporting biopharma scientific research data analytics (software platforms)
Functional
Skills:
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
- Strong understanding of data modeling, data warehousing, and data integration concepts
- Strong 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:
- Excellent critical-thinking and problem-solving skills
- Strong communication and collaboration skills
- Demonstrated awareness of how to function in a team setting
- Demonstrated presentation skills
