P-4215 Staff Data Analytics Engineer

About the role:

10x is looking for an outstanding Staff Data Analytics Engineer to join the Manufacturing Systems Engineering (MSE) team. This pivotal position sits at the intersection of MSE and the Production Engineering team, ensuring robust data pipelines and advanced analytics solutions for the Operations team. 

Individuals applying for this position must be self-starters, strategic thinkers, action driven, flexible in changing direction and methods, thrive in a fast-paced environment, excel at managing multiple priorities, succeed in communicating with all levels within the organization and provide immediate contribution.  Ideal candidate will come from a science or engineering background with a track record of developing visualization tools and analytics, while being proficient in ETL and data warehousing.The ideal candidate has a science or engineering background and is proficient in ETL and data warehousing. They also have a proven ability to develop visualization tools, dashboards and complex analytics.

What you will be doing:

• Work closely with internal stakeholders (e.g., customer-facing support teams, centralized data team, finance, logistics, manufacturing engineering, quality, process development and R&D) to understand project objectives and analytical needs.  Provide leadership to integrate deep domain knowledge with cross functional expertise to influence technical strategy.
• Partner with the stakeholders, ensuring minimal disruption to data workflows, and implement and optimize ETL processes to develop and scale data integration and analysis of quality-related data (quality control, nonconformances, manufacturing data) and from various sources.
• Drive automation of data ingestion, transformation, and validation processes for operations/manufacturing large-scale data sources. Leverage scripting and infrastructure-as-code to increase efficiency and reliability.
• Create and maintain frameworks and analysis tools and dashboards that enable innovation and productivity across teams. 
• Contribute to fast pace ad-hoc CAPA investigations and remediation
• Provide data analysis support for the process development team
• Maintain accurate and detailed records of testing, conduct in-depth data analysis, and clearly document data engineering processes, standards, and best practices to ensure knowledge sharing and maintainability.
• Continuously evaluate and adopt new technologies and tools to improve data engineering processes and efficiency.

 Minimum Requirements:

• Degree in Engineering, Computer science, Data science, Statistics, or related field 
• BS with 10+ years of experience, or MS / PhD with 5-8 years of experience.
• Experience with ETL development and proficiency in SQL
• Experience with data analytics and implementing data visualization 
• Understanding of manufacturing statistical process control and monitoring. 

Preferred Skills & Experience: 

• Experience in developing process controls for the manufacture of successful life science products.
• Life science and/or chemical engineering background
• Proficiency in programming languages such as Python and JavaScript
• Experience with cloud infrastructure, such as AWS or GCP
• Experience with Snowflake Data Warehousing Technology and modeling
• Experience with standard statistical analysis software (e.g. JMP, R, CHARTrunner, Minitab, Matlab)
• Strong problem-solving skills and attention to detail
• Excellent communication and collaboration skills, with the ability to work effectively in a multidisciplinary team environment
• Desire to be part of a rapidly evolving organization, with a compelling technology, and taking products and processes to the next level
• Working knowledge of Lean and/or Six Sigma methodologies. 

Nice to have

• Familiarity with using data platform tools Coalesce, DBT ,  Datafold or others
• Familiarity with the GitHub CI/CD process.

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