Senior Full Stack Cloud Engineer - Smart Grid

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

• 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

• 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 (Sage Maker, Bedrock, etc.)

• Guide and mentor junior developers and team members
• Lead technical design reviews and architecture decisions
• Drive best practices for cloud development and Dev Ops methodologies
• Collaborate with cross-functional teams to translate business requirements into technical solutions
• Champion bias-for-action culture while maintaining high technical standards

• AWS cloud services ecosystem (EC2, Lambda, IoT Core, Kinesis, S3, Dynamo
  
  DB, Redshift, Glue, RDS, Bedrock etc.)
• Experience with Programming languages (Python, Java, C#, Go, JavaScript/Type Script)
• AWS AI/ML services (Sage Maker, 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, Influx
  
  DB, or similar)
• Data engineering and ETL/ELT pipeline development
• Experience with Sonar Qube
• 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