Cognizant
Senior Full Stack Cloud Engineer - Smart Grid 2.0
Cognizant, West Palm Beach, Florida, United States, 33412
Roles and Responsibilities
Cloud & IoT Solutions Implementation (50%)
Design and implement secure & scalable cloud-native architectures (Microservices, Serverless, Container) using comprehensive AWS stack
Build end-to-end IoT solutions from device connectivity through data analytics
Develop real-time streaming data pipelines from hardware devices and sensors
Design and implement time-series database solutions and data engineering frameworks
Create robust proof-of-concepts (POCs) from ground-up using AWS services Big
Data & Analytics Platform Development (25%)
Implement and optimize big data solutions using Amazon Kinesis, Glue, EMR, Redshift, and Timestream
Design data lakes and warehouses for massive IoT data ingestion and analysis
Build real-time analytics dashboards and reporting frameworks
Optimize query performance and data processing workflows to match business needs
Develop data governance and security frameworks aligning with enterprise guidelines AI/ML
Implementation & Innovation (15%)
Lead implementation of AI-driven solutions for smart grid applications
Develop predictive analytics and anomaly detection systems for grid operations working with Data Scientists
Deploy, optimize and integrate Generative AI, machine learning, deep learning, and natural language processing models for high value use cases
Prototype AI solutions using AWS AI/ML services (SageMaker, Bedrock, etc.)
Technical Leadership & Mentoring (10%)
Guide and mentor junior developers and team members
Lead technical design reviews and architecture decisions
Drive best practices for cloud development and DevOps methodologies
Collaborate with cross-functional teams to translate business requirements into technical solutions
Champion bias-for-action culture while maintaining high technical standards
Basic Qualifications
AWS cloud services ecosystem (EC2, Lambda, IoT Core, Kinesis, S3, DynamoDB, Redshift, Glue, RDS, Bedrock etc.)
Experience with Programming languages (Python, Java, C#, Go, JavaScript/TypeScript)
AWS AI/ML services (SageMaker, Bedrock, Comprehend, Rekognition)
Big data technologies (Amazon EMR, Redshift, Spark, Hadoop)
Deploying machine learning models, deep learning algorithms
IoT knowledge including device connectivity, protocols, and data ingestion
Real-time streaming data processing and analytics
Time-series databases (Amazon Timestream, InfluxDB, or similar)
Data engineering and ETL/ELT pipeline development
Experience with SonarQube
IoT platforms and edge computing solutions
Industrial communication protocols (MQTT, OPC-UA, Modbus, DNP3)
Containerization and orchestration (Docker, Kubernetes, ECS)
Please note, this role is not able to offer visa transfer or sponsorship now or in the future
#J-18808-Ljbffr
Design and implement secure & scalable cloud-native architectures (Microservices, Serverless, Container) using comprehensive AWS stack
Build end-to-end IoT solutions from device connectivity through data analytics
Develop real-time streaming data pipelines from hardware devices and sensors
Design and implement time-series database solutions and data engineering frameworks
Create robust proof-of-concepts (POCs) from ground-up using AWS services Big
Data & Analytics Platform Development (25%)
Implement and optimize big data solutions using Amazon Kinesis, Glue, EMR, Redshift, and Timestream
Design data lakes and warehouses for massive IoT data ingestion and analysis
Build real-time analytics dashboards and reporting frameworks
Optimize query performance and data processing workflows to match business needs
Develop data governance and security frameworks aligning with enterprise guidelines AI/ML
Implementation & Innovation (15%)
Lead implementation of AI-driven solutions for smart grid applications
Develop predictive analytics and anomaly detection systems for grid operations working with Data Scientists
Deploy, optimize and integrate Generative AI, machine learning, deep learning, and natural language processing models for high value use cases
Prototype AI solutions using AWS AI/ML services (SageMaker, Bedrock, etc.)
Technical Leadership & Mentoring (10%)
Guide and mentor junior developers and team members
Lead technical design reviews and architecture decisions
Drive best practices for cloud development and DevOps methodologies
Collaborate with cross-functional teams to translate business requirements into technical solutions
Champion bias-for-action culture while maintaining high technical standards
Basic Qualifications
AWS cloud services ecosystem (EC2, Lambda, IoT Core, Kinesis, S3, DynamoDB, Redshift, Glue, RDS, Bedrock etc.)
Experience with Programming languages (Python, Java, C#, Go, JavaScript/TypeScript)
AWS AI/ML services (SageMaker, Bedrock, Comprehend, Rekognition)
Big data technologies (Amazon EMR, Redshift, Spark, Hadoop)
Deploying machine learning models, deep learning algorithms
IoT knowledge including device connectivity, protocols, and data ingestion
Real-time streaming data processing and analytics
Time-series databases (Amazon Timestream, InfluxDB, or similar)
Data engineering and ETL/ELT pipeline development
Experience with SonarQube
IoT platforms and edge computing solutions
Industrial communication protocols (MQTT, OPC-UA, Modbus, DNP3)
Containerization and orchestration (Docker, Kubernetes, ECS)
Please note, this role is not able to offer visa transfer or sponsorship now or in the future
#J-18808-Ljbffr