Principal Solutions Engineer, Data Analytics

Key Skills

C# Programming, Data Analytics, Data Warehousing, Database, Design, ETL frameworks, Grafana, GraphQL, JavaScript, JMP, Kubernetes-K8s, Leadership Skill, MongoDB, NoSQL, PostgreSQL, Python Programming, R Programming, Rust, SAS, SQL, Swift

Job Description

The Principal Solutions Engineer, Data Analytics will contribute to full stack Data Analytics software configurations for global and regional Data Analytics Product Groups. This role will establish proficiency in Data Analytics Computer Science supporting pharmaceutical and bio-pharmaceutical data sciences/advanced analytics. As directed by Global Manufacturing Science and Technology Data Analytics leadership, the incumbent contributes to global efforts by supporting, developing, and maintaining tools and software solutions key to enabling statistical modeling, visualization, reporting, and interpretation of results. Contribute to the execution of Quality Risk Assurance based data integrity and validation reports with appropriate business acumen for stakeholder interpretations and qualifications.

The Principal Solutions Engineer, Data Analytics will help provide analysis-ready batch contextualized vector and attribute data engineering to statisticians and data scientists for applications of generalized linear modeling, time-series multivariate statistics including Principal Components Analysis and Partial Least Squares, QC test method validations, ANOVA/means comparisons, and univariate and multivariate Statistical Process Control (SPC) methodologies.

Requirements

• Bachelor’s Degree in Computer Science, Information Science, Information Technology, Database Design and Implementation, or related field.
• In addition to relevant Bachelor's Degree, a minimum of seven (7) years applied computer science/data analytics experience in manufacturing industry, pharmaceutical, bio-pharmaceutical or related organization.
• OR
• Relevant Master's Degree and a minimum of four (4) years applied computer science/data analytics in manufacturing industry, pharmaceutical, bio-pharmaceutical or related organization.
• Previous experience directly in pharma and life science full stack architecture and data management is a prioritized preference.
• Expertise in computer science disciplines related to pharmaceutical/biological life science industry is highly preferred.
• Academic and Demonstrated Knowledge of C#, SQL, Graph, GO, Javascript, NoSQL,
• Recommended software experience: OSIsoft PI, PI AF, Libre, ETL Data Warehouse Design and Implementation, Grafana, SIMCA, SIMCA-online, SAS JMP, Visual Studio, MS DB Mgmt Studio, MongoDB, PostgreSQL, Kubernetes, RedHat OpenShift.
• Desired Proficiency: R, Python, Rust, Swift.
• Knowledge of mathematics and computer science theory and application of statistical methodologies relative to process performance analytics and data sciences preferred.
• Ability to perform tasks typically expected of a Data Engineer.
• Ability to convey analytical thinking as well as business acumen and technical knowledge.
• Ability to work effectively as part of a team and manage project(s) from a data management perspective.

Duties & Responsibilities

• Executes the duties of data management and software configurations for complex pharmaceutical batch analytics.

• Responsible for maintaining a general level of business acumen and data science knowledge to ensure the fit, form, and function of data science software.
• Collaborates with Global MSAT Data Analytics management, team, and stakeholders, to set and achieve project goals.
• For projects of diverse complexity, provides configuration support for all process historians, ERP, LIMS, and Electronic Batch Systems.
• Helps perform feasibility studies for commercial and open-source software technologies identified by team leadership with the intent of more effective and efficient data science user experiences across multiple sites and programs.
• Conducts periodic review of LAN, WAN, Edge servers in regional data centers and software architectures relative to data transfer rates and create data flow latency summarizations to ensure optimum user experiences for data scientists and local users.
• Participates in agile software and data management standards to support advanced data science programs and product groups.
• Receives feedback and adjusts program management effectiveness from Global MSAT, Strategic site stakeholders and leadership, IT Governance bodies, and Global Engineering.
• Clearly communicates all aspects of data management requirements and functionality relative to Advanced Analytics outcomes to a diverse group of global stakeholders at all levels and locations of the organization.
• Establishes proficiency and industrial knowledge though primary literature, trade forums, and user meetings.
• Recommends and applies new/emerging technologies to ongoing MSAT projects enhancing Global MSAT Data Analytics Product Groups when profitable.
• Cultivates sound partnerships with internal and external stakeholders and colleagues.
• Engages and collaborates with international colleagues to promote international harmonization.
• Participates in internal or external working groups.

Desired Skills, Experience and Abilities

Additional Requirements:

• Ability to determine appropriate database design, development, and configurations to deliver efficient architectural approach for advanced analytics.
• Demonstrated experience pro-actively identifying/detecting design issues and recommending solutions in global architectures and database design and implementations supporting global networks.
• Leadership experience managing others to successful outcomes with earned value.

Our Company

At Boehringer Ingelheim we develop breakthrough therapies that improve the lives of both humans and animals. Founded in 1885 and family-owned ever since, Boehringer Ingelheim takes a long-term perspective. Now, we are powered by 52,000 employees globally who nurture a diverse, collaborative and inclusive culture. We believe that if we have talented and ambitious people who are passionate about innovation, there is no limit to what we can achieve.