Sr. Software Engineer

Cognizant; Chennai; On-site; INR 1,200,000 - 1,800,000; 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 Golden Batch analytics. You will develop data models for manufacturing analytics and implement both real-time streaming and batch processing across Trio Line data.

The role requires hands-on experience with Spark, Python, SQL, and cloud services (Azure). You will ensure data quality, lineage, and governance while collaborating with cross-functional teams to

Qualifications

• Hands-on data engineering with Spark Python SQL
• Experience with real-time streaming like Kafka Streams or Spark Streaming
• Cloud data platforms (Azure Data Factory, Databricks)
• Strong understanding of manufacturing data models and telemetry patterns
• Knowledge of data governance, lineage, and metadata management
• Experience with data quality frameworks and automated validation
• Familiarity with GxP data integrity and audit trails
• Ability to translate business requirements into technical solutions

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 data.
• Implement real-time streaming and batch processing for Trio Line operational data.
• Build and maintain data lake and data warehouse structures for analytical use cases.
• Ensure data quality through validation rules and anomaly detection.
• Implement data lineage tracking and audit trails compliant with GxP requirements.
• Optimize pipeline performance to meet throughput and latency requirements.
• Collaborate with the Senior Techno Functional Consultant to align data architecture with business needs.

Skills

Apache Spark

Python

SQL

Kafka Streams

Spark Streaming

Azure Data Factory

Azure Databricks

GxP governance

Tools

Delta Lake

Apache Iceberg

Power BI

Grafana

Job description

Job Summary

Design and build production-grade data pipelines for OEE metrics Connected Worker events and Golden Batch analytical data.

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.