Associate Data Engineer - R&D Omics

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 you

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.