Data Engineer Associate

Bosch Group•Roseville, CA

2d•$75,000 - $85,000•Onsite

About The Position

The Data Engineer for Digital Manufacturing is responsible for designing, building, and maintaining the data architecture and infrastructure that drives our smart factory initiatives. This role is central to our Industry 4.0 strategy, ensuring that robust, scalable systems are in place to support advanced analytics, machine learning, and process automation. The ideal candidate will possess a deep understanding of modern data technologies, DevOps principles, and have a passion for deploying AI-driven solutions in a manufacturing environment.

Requirements

Diploma/Bachelor in computer science or equivalent
1-3 years professional working experience as an administrator for Oracle/MS SQL , Hadoop clusters.
Experience with Oracle products, Grid/Cloud Control, RAC, ASM, Hadoop, gethue.
Experience with RedHat Linux and Veritas Cluster, Volume Manager, SAN storage and TSM backup
Experience with cloud platforms (e.g., Azure, AWS, GCP) and their data services.
Strong technical documentation, interpersonal, presentation and communication skills.
Able to participate in 24x7 on-call support

Responsibilities

Day-to-day support, administer and monitor Oracle and MS SQL databases across Bosch semiconductor network.
Installs and configures databases, monitoring performance, ensuring data consistency, and troubleshooting issues.
Design, Build and Run Oracle/MS SQL environments and maintain DB’s performance and availability.
Perform Oracle/MS SQL health check, troubleshooting and performance tuning.
Collaboration with Worldwide DBA team in EMEA and America region.
Design, build, and run scalable data architecture, including automated data pipelines and ETL/ELT processes for large-scale data processing.
Manage and administer a variety of data storage technologies, including relational (e.g., SQL) and NoSQL databases, ensuring data integrity, performance, and security.
Implement and manage infrastructure as code using DevOps methodologies; utilize tools like Docker and container orchestration for deploying applications and services.
Develop and deploy automation for data workflows, system monitoring, and operational tasks to improve efficiency and reliability.
Collaborate with data scientists and manufacturing engineers to deploy, monitor, and maintain AI/ML models in a production environment (MLOps).
Work closely with other infrastructure, security, and application teams to ensure the seamless delivery of data services that meet performance targets and SLAs.
Further the development of system and operational concepts for data infrastructure and its integration with manufacturing applications.
Create and maintain strong technical documentation for data systems, processes, and architecture.