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Form of workJob Description
Position: MLops Engineer
Location : Hybrid role in Bay Area CA (2 days in a week to office)
Duration : 12 + Months
Description
Key Responsibilities
Minimum Requirements
Preferred Qualifications
Location : Hybrid role in Bay Area CA (2 days in a week to office)
Duration : 12 + Months
Description
- Genentech seeks an experienced Senior Data and MLOps Engineer to own the design and growth of a next generation AWS data lake, data pipelines, data quality metrics and productizing with Client Ops. The role will lead the development of infrastructure that enables the availability of data sets derived from different systems and this data engineer will collaborate with interdisciplinary teams throughout Site Services and IT. Data is at the center of every insight we develop as we create business analytics and data science / AI solutions that serve the needs of our partners. The data lake is a foundational system in supplying data as an asset, and the successful candidate will share in the ownership of the technical vision and direction of using data for advanced analytics, data science and insight products and services.
Key Responsibilities
- Conceptualize and own the design, implementation and operations of the next-generation data lake containing complex Genentech data from any Genentech business areas and operating within a global environment
- Conceptualize and own the data architecture for multiple large-scale projects across analytics, automation, data science and artificial intelligence, while evaluating design and operational cost-benefit tradeoffs within systems across different partnered business areas
- Solve challenging data integration problems for complicated and diverse data sets, utilizing and coding optimal ETL patterns, frameworks, query techniques, and sourcing / merging from structured and unstructured data sources
- Implement and optimize data pipelines, data quality metrics, and systems to facilitate easier development of data artifacts and support machine learning systems at scale
- Design and develop MLOps Infrastructure to build, train and deploy Client Models using cloud native services
- Design and develop secure, scalable, high-performance and reliable data and analytics solutions in a cloud platform (preferably AWS)
- Define and manage SLAs for all data sets in designated areas of ownership
- Collaborate with engineers, business managers, and data scientists from different business areas globally to understand complex data needs and provide key data insights in meaningful ways
- Identify and evaluate new technologies to improve performance, maintainability, and reliability of data systems.
Minimum Requirements
- Bachelor's degree in Information Systems, Computer Science, Computer Engineering, or related field with additional experience
- 5-8 years of experience as a Data Engineer, or in a similar role
- Experience designing, evolving and running data lakes with complex data and multiple customer groups
- Experience developing data pipelines using data from heterogeneous data sources (eg. AWS, Oracle, SAP, Salesforce, etc.)
- Experience with data modeling, data warehousing, and building data pipelines
- Experience implementing and monitoring data quality metrics in a data governance environment
- Experience with MLOps
- Experience with AWS, AWS Data Engineering and MLOps tools and services (ie: S3, Redshift, Athena, Glue, Lambda, SageMaker etc)
- Experience with software development and version control systems
- Experience designing and building large-scale technology products
- Experience leading engineering discussions around technology decisions
- Ability to understand complex problems and collaboratively develop ad hoc solutions in rapidly changing environment
- Strong technical communication skills
Preferred Qualifications
- Master's degree in Information Systems, Computer Science, Computer Engineering, or related field and additional experience.
- Experience with secure data warehousing and robust ETL techniques
- Knowledge and experience in analytics, data science, machine learning and/or NLP
- Strong proficiency in SQL, Python and PySpark
- Experience understanding the perspectives of team members from other disciplines or backgrounds
- Experience analyzing business needs and opportunities
