Sr. Software Engineer

Cognizant; Chennai Metropolitan Area; On-site; INR 900,000 - 1,500,000; Full time

Job summary

Cognizant is seeking a data engineer to design and build production-grade data pipelines for OEE metrics, connected worker events, and batch analytics in manufacturing.

You will develop data models for batch records, equipment telemetry, and worker activity, and implement both real-time streaming and batch processing for Trio Line data. This role emphasizes data quality, governance, and alignment with business needs.

Qualifications

• 5+ years hands-on data engineering with Spark Python and SQL.
• Experience with real-time streaming using Kafka Streams or Spark Streaming.
• Cloud data platforms such as Azure Data Factory and Azure Databricks.
• Strong knowledge of manufacturing data models time-series data and telemetry.
• Familiarity with data governance frameworks data lineage tracking and metadata management.
• Experience with data quality frameworks and automated validation pipelines.
• Familiarity with GxP data integrity including ALCOA Plus principles.

Responsibilities

• Design and build production-grade data pipelines for OEE metrics, Connected Worker events, and Golden Batch data.
• Develop data models for manufacturing analytics including batch records, equipment telemetry, and worker activity.
• Implement real-time streaming and batch data processing for Trio Line operational data.
• Build and maintain data lake and data warehouse structures optimized for GMSx analytics.
• Ensure data quality through validation rules, anomaly detection, and data integrity checks for manufacturing data.
• Implement data lineage tracking, metadata management, and audit trails for GxP compliance.
• Optimize data pipeline performance to meet production throughput and latency requirements.
• Collaborate with the Senior Techno Functional Consultant to align data architecture with business requirements and use case definitions.

Skills

Apache Spark

Python

SQL

Kafka Streams

Spark Streaming

Azure Data Factory

Azure Databricks

GxP Data Integrity

ALCOA Plus

Data Modeling

Tools

Kafka

Delta Lake

Apache Iceberg

Job description

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.