Mgr Data Engineer - Research Data and Analytics

Job Description

Lead, manage, and mentor a high-performing team of data engineers Design, develop, and implement data pipelines, ETL processes, and data integration solutions Take ownership of data pipeline projects from inception to deployment, manage 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 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 What we expect of you We are all different, yet we all use our unique contributions to serve patients. The [vital attribute] professional we seek is a [type of person] with these qualifications. Basic Qualifications: Doctorate Degree OR Master s degree with 4 - 6 years of experience in Computer Science, IT, Computational Chemistry, Computational Biology/Bioinformatics or related field OR Bachelor s degree with 6 - 8 years of experience in Computer Science, IT, Computational Chemistry, Computational Biology/Bioinformatics or related field OR Diploma with 10 - 12 years of experience in Computer Science, IT, Computational Chemistry, Computational Biology/Bioinformatics or related field Preferred Qualifications: 3+ 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 Able to engage with business collaborators and mentor team to develop data pipelines and data models Good-to-Have Skills: A passion for tackling complex challenges in drug discovery with technology and data Good understanding of data modeling, data warehousing, and data integration concepts Good 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 Good communication and collaboration skills Demonstrated awareness of how to function in a team setting Demonstrated presentation skills