Associate Data Engineer-Research Data and Analytics

[Associate Data Engineer]

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 stakeholders. The ideal candidate possesses experience in the pharmaceutical or biotech industry, demonstrates strong technical skills, has experience with big data technologies, and understands data architecture and ETL processes

• 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

Basic Qualifications:

• Bachelors 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)

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

• 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

• Databricks Certified Data Engineer Professional preferred

• 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