Sr Data Engineer - Research Data and Analytics

In this 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, is proficient with big data technologies, and has a deep understanding of data architecture and ETL processes.

Roles & Responsibilities

• Data Pipeline Development:
• Design, develop, and implement data pipelines, ETL/ELT processes, and data integration solutions.
• Take ownership of data pipeline projects from inception to deployment, managing scope, timelines, and risks.
• Develop and maintain data models for biopharma scientific data, data dictionaries, and other documentation to ensure data accuracy and consistency.
• Optimize large datasets for query performance.
• Collaboration and Solution Design:
• 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.
• Troubleshooting and Best Practices:
• Identify and resolve complex data-related challenges.
• Adhere to best practices for coding, testing, and designing reusable code/components.
• Innovation and Process Improvement:
• Explore new tools and technologies that will help improve ETL platform performance.
• Participate in sprint planning meetings and provide estimations on technical implementation.
• Maintain comprehensive documentation of processes, systems, and solutions.

Basic Qualifications and Experience

• Doctorate Degree; OR
• Master's degree with four to six years of experience in Computer Science, IT, Computational Chemistry, Computational Biology/Bioinformatics, or a related field; OR
• Bachelor's degree with six to eight years of experience in Computer Science, IT, Computational Chemistry, Computational Biology/Bioinformatics, or a related field; OR
• Diploma with ten to twelve years of experience in Computer Science, IT, Computational Chemistry, Computational Biology/Bioinformatics, or a related field.

Preferred Qualifications and Experience

• Over three 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, and 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.
• Understanding of data governance frameworks, tools, and best practices.

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