Associate Data Engineer Graph - Research Data and Analytics

In this vital role you will be part of Researchs Semantic Graph. Team is seeking a dedicated and skilled Data Engineer to design, build and maintain solutions for scientific data that drive business decisions for Research. You will build scalable and high-performance, graph-based, data engineering solutions for large scientific datasets and collaborate with Research partners. The ideal candidate possesses experience in the pharmaceutical or biotech industry, demonstrates deep technical skills, has experience with semantic data modeling and graph databases, 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 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 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

• Bachelors degree and 1to 3 years of Computer Science, IT, Computational Chemistry, Computational Biology/Bioinformatics or related field experience OR
• Diploma and 4 to 7 years of Computer Science, IT, Computational Chemistry, Computational Biology/Bioinformatics or related field experience

Must-Have Skills:

• Advanced Semantic and Relational Data Skills: Proficiency in Python, RDF, SPARQL, Graph Databases (e.g. Allegrograph), SQL, relational databases, ETL pipelines, big data technologies (e.g. Databricks), semantic data standards (OWL, W3C, FAIR principles), ontology development and semantic modeling practices.
• Hands on experience with big data technologies and platforms, such as Databricks, workflow orchestration, performance tuning on 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
• Experience with system administration skills, such as managing Linux and Windows servers, configuring network infrastructure, and automating tasks with shell scripting. Examples include setting up and maintaining virtual machines, troubleshooting server issues, and ensuring data security through regular updates and backups.
• 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 user documentation in Confluence

• Databricks Certified Data Engineer Professional preferred

• Excellent critical-thinking and problem-solving skills
• Good communication and collaboration skills
• Demonstrated awareness of how to function in a team setting
• Demonstrated presentation skills