Job Summary
Design and build production-grade data pipelines for OEE metrics Connected Worker events and Golden Batch analytical data
Develop data models for manufacturing analytics including batch records equipment telemetry and worker activity data
Implement both real-time streaming and batch data processing for Trio Line operational data
Build and maintain data lake/warehouse structures optimized for GMSx analytical use cases
Responsibilities
Design and build production grade data pipelines for OEE metrics Connected Worker events and Golden Batch analytical data.
Develop data models for manufacturing analytics including batch records equipment telemetry and worker activity data.
Implement both real time streaming and batch data processing for Trio Line operational data.
Build and maintain data lake and data warehouse structures optimized for GMSx analytical use cases.
Ensure data quality through validation rules anomaly detection and data integrity checks for manufacturing data.
Implement data lineage tracking metadata management and audit trail capabilities compliant with GxP requirements.
Optimize data pipeline performance to meet production throughput and latency requirements.
Collaborate closely with the Senior Techno Functional Consultant to align data architecture with business requirements and use case definitions.
Required Qualifications and Experience
5 plus years of hands on data engineering experience with Apache Spark Python and SQL.
Experience with real time data streaming technologies such as Kafka Streams Spark Streaming or equivalent platforms.
Cloud data platform expertise including Azure Data Factory Azure Databricks or equivalent cloud native data services.
Strong understanding of manufacturing data models time series data and equipment telemetry patterns.
Knowledge of data governance frameworks data lineage tracking and metadata management.
Experience with data quality frameworks and automated data validation pipelines.
Familiarity with GxP data integrity requirements including ALCOA Plus principles electronic records and audit trails.
Ability to work in cross functional teams and translate data requirements from business stakeholders into technical solutions.
Preferred Qualifications
Experience with pharmaceutical manufacturing data including batch records process parameters and equipment logs.
Familiarity with Unified Namespace data architecture and Manufacturing Data Fabric concepts.
Experience with Delta Lake Apache Iceberg or similar lakehouse technologies.
Knowledge of statistical process control and Golden Batch analysis methodologies.
Experience with data visualization tools such as Power BI and Grafana for manufacturing dashboards.
关于高知特 (Cognizant)
高知特(Cognizant)（纳斯达克代码：CTSH）作为一家AI Builder和相关技术服务提供商，致力于通过打造全栈AI解决方案，帮助企业将人工智能投资转化为实际价值。公司凭借深厚的行业经验、流程优化和工程技术专长，将企业独特的业务场景融入科技系统，赋能组织释放人才潜能，推动切实成果，并帮助全球企业在瞬息万变的环境中保持领先。如需了解更多详情，敬请访问 cognizant.ai 或关注@cognizant。
补充雇佣信息
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