Consult Blue

We specialize in delivering backend and data engineering solutions with large or time critical requirements using AWS, GCP or Azure.

Architecture and Backend:

• Architecture, back-end and devops for vendor intelligence system based on email analysis. GSuite Admin SDK sync and GMail email integration on multiple AWS VPCs, PostgreSQL, Lambda for external data gathering, Python based ETL, Node API to expose data to front-end, devops using Terraform and Ansible
• Architecture and back end for cyber security insurance intelligence: multi layer AWS Lambda orchestration with multi region deployment.
• System for monitoring obstruction lights: SNMP and MQTT communication with devices, Python Flask back end, Vue frontend
• System for head-hunting and recruiting. Responsive React single page app. Integrated with Firebase for user management, connected to LinkedIn and Facebook for social sharing / posting / login and coupled with Stripe and Google Functions (NodeJS) for payment handling. REST API backend based on GCP, Datastore, Google Storatge. Handled 200M+ candidate profiles, 1TB raw data in JL format.
• System for North Carolina voter files analysis. 7M voters, importing by county, clean up, various analysis and filters. Front-end on AngularJS and Bootstrap, back-end with Flask on Google Compute Engine, Cloud Storage and Cloud SQL (MySQL)

IoT:

• IoT system: collected data via AWS IoT Core, process via Lambda including threshold detection using finite state machine (FSM), store it to DynamoDB and S3, create IoT Analytics and Quicksight reporting. Monitor using Lambda.
• FANET (Flying Ad-hoc Network) protocol translator implementation using AWS IoT Core and AWS Lambda.
• Python framework for controlling humanoid robots, data acquisition from Lidar, RGB cameras, Sonars for robot navigation, voice interaction using Google Cloud Services and Wit.ai for natural language understanding
• Mobile application for IoT data monitoring from smart watches, blood pressure monitors, smart scales and various Zigbee sensors, with Angular JS front-end and NodeJS back-end, using Firebase Cloud Messaging for push notifications and ported using Apache Cordova
• Raspberry PI system using Miura card reader via Bluetooth to process payments.

Data Engineering:

• Data Lake environments synchronizations. Generating AWS S3 sync scripts, SQL metadata sync (AWS Aurora / PostgreSQL) and SQL scripts for adding partitions to Athena tables, AWS Glue jobs were used for transforming row data into partitioned files (parquet). Pyspark library for development.