Almas Mohammed

Skills

Skill Area Tools / Technologies
Core Programming Python, Golang, C, C++, Perl, Embedded C, OOP, Algorithm Design, TCP/IP
Web Frameworks Django (MVT, REST APIs, Async, Caching), Flask (Blueprints, JWT, REST), FastAPI, Node.js, AngularJS, ASP.NET
Front-End Technologies React.js, AngularJS, HTML5, CSS3, Bootstrap, AG Grid, JSP, QT, PHP
API Development REST APIs, GraphQL, FastAPI, Flask, Django, Node.js, JWT, Schema Validation, Token Security, API Gateway
Event Streaming / Messaging Kafka, Google Pub/Sub, Apache Storm, Protobuf, JSON, Dead-letter Topics, Versioned Schemas, Flow Control
Data Engineering & ETL PySpark, Apache Airflow, SnowSQL, Glue, Databricks Autoloader, Sqoop, Storm, GCS, S3, ADLS, Delta Lake, Pandas, NumPy
Databases (RDBMS & NoSQL) PostgreSQL, MySQL, Cosmos DB, DynamoDB, MongoDB, Redis, Snowflake, BigQuery, Redshift, TimescaleDB
ORM Tools SQLAlchemy, Django ORM
Cloud Platforms AWS (EC2, S3, Lambda, IAM, Route 53, Glue, SNS, SQS, CloudWatch, ECS), Azure (AKS, Cosmos DB, Blob Storage, Logic Apps, AAD, PaaS), GCP (BigQuery, Pub/Sub, Stackdriver, Cloud Functions, IAM)
IaC & Provisioning Terraform, CloudFormation, Ansible, Puppet, Chef, Azure Bicep
DevOps & CI/CD Jenkins, Git, GitHub, SVN, CVS, Azure DevOps, Docker, Kubernetes, OpenShift, Octopus, GitOps, CI/CD Pipelines (Python, Go), Paired Development, BDD
Containerization & Orchestration Docker, Kubernetes, ECS, AKS, OpenShift
Workflow Orchestration Apache Airflow, Camunda BPMN 2.0, Azure Logic Apps
Machine Learning / AI / NLP Scikit-learn, PyTorch, ML Preprocessing (Scaling, Encoding), Pandas, NumPy, Real-time ML Pipelines, Anomaly Detection, Recommendation Engines, NLP Integration
Testing & QA Unit Testing, Integration Testing, Regression Testing, TDD, Load Testing, BDD
Monitoring & Observability CloudWatch, Stackdriver, GCP Monitoring, Grafana, Custom Dashboards, Real-time Logging, Metrics Collection
Infrastructure Scripting Shell, Bash, Perl, Python, Go, Boto3, Automation Scripts
Security & Governance IAM (AWS, GCP), Azure Active Directory, Role-Based Access Control (RBAC), Unity Catalog, Token Validation, Data Masking, HIPAA/GDPR Compliance
Geospatial & Visualization ArcGIS, GeoPandas, CartoPy, Tableau, Power BI, Matplotlib, Custom Dashboards
Serialization & Data Formats JSON, XML, YAML, Protobuf, CSV, Parquet, Pickle, urllib2
Data Quality & Schema Mgmt Pydantic, Cerberus, Metadata Configs, Schema Evolution, Data Cataloging, Data Quality Alerts
Business Intelligence BigQuery SQL, Databricks SQL, Tableau, Power BI, Redshift
Software Architecture Modular Microservices, Docker + Terraform for Decoupling, Python/Go Service Migration, Serverless (GCP + Azure), Scalable SaaS, Event-Driven Design
Full-Stack Data Workflows Ingestion → Transformation → Analytics using Flask, Pandas, PySpark, GCS, BigQuery, Snowflake, Databricks, Cosmos DB
CI/CD + Monitoring Dashboards Jenkins Pipelines, Kubernetes Dashboards, Git-based Workflows, Azure DevOps, Monitoring via Cloud Logs, SaaS Metrics
Data Lake Architecture GCS/S3/ADLS, Delta Lake, Schema Mapping, Lifecycle Management, Metadata Driven Ingestion, Real-time Streaming (Kafka/Storm)
Network & Communication VPC Peering, VPN Tunnels, Global Load Balancers, Secure Messaging, Real-Time HTTP APIs
SRE & Performance Site Reliability Engineering (SRE), Performance Dashboards, Threshold Monitoring, System Health Metrics
Automation & Compliance Automated ETL, Event Triggers, OFAC Compliance Messaging, Secure Workflows via Logic Apps & Chef, Governance Pipelines
Hybrid Web/Cloud Platforms Python 3, Django, Kafka, Terraform, C++, Angular, React, PHP, Hybrid Cloud Ecosystems (AWS, Azure, GCP)

About

• 12+ years of experience architecting enterprise-scale distributed healthcare, telecommunications, and technology platforms as a Senior Python Engineer, designing resilient microservices with Python, Django, FastAPI, and Flask, integrating PostgreSQL, MongoDB, Redis, Kafka, Snowflake, and Databricks, and orchestrating Docker and Kubernetes deployments across AWS and GCP environments.
• Proficiency in DevOps enablement for Python applications across healthcare and telecom platforms through Docker containerization, Kubernetes orchestration, Terraform automation, CI/CD pipeline design, and multi-environment AWS and GCP release governance.
• Expertise in backend scalability through Core Python multithreading, SQL indexing optimization, MongoDB replication, and GCP managed services such as Cloud SQL and Kubernetes Engine, integrating Kafka and Google Pub/Sub across AWS, Azure, and GCP ecosystems while containerizing applications with Docker and orchestrating distributed platforms.
• Knowledge of enterprise API governance within healthcare and telecom ecosystems, including REST architecture, GraphQL schema strategy, OAuth2 authentication, JWT authorization, rate-limiting mechanisms, secure middleware development in Python, observability via ELK and Prometheus, and scalable application frameworks using Core Python and Django.
• Experience building enterprise observability platforms integrating ELK logging, Prometheus monitoring, distributed tracing for Python microservices, Kafka monitoring, PostgreSQL diagnostics, and AWS and GCP infrastructure analytics.
• Expertise in full-stack solution engineering with Python backend services (Django, Flask, FastAPI), React, and Node.js integrations, modernizing legacy healthcare and telecom monoliths into scalable microservices, refining PostgreSQL execution plans, restructuring MongoDB schemas, integrating Redis caching layers, coordinating Kafka event orchestration, and automating infrastructure through Terraform across AWS and GCP regulated environments.
• Knowledge of scalable application frameworks using Core Python and Django within healthcare and telecom domains, implementing SQL replication, MongoDB sharding, and utilizing GCP auto-scaling capabilities to sustain high-traffic systems with optimized backend execution.
• Experience developing highly available APIs with Python, FastAPI, and Django for healthcare systems, enabling asynchronous processing, Redis caching optimization, PostgreSQL tuning, MongoDB aggregation pipelines, and Kafka-based orchestration within cloud ecosystems.
• Expertise in large-scale Python performance engineering and architectural strategy across healthcare and telecom workloads, conducting memory profiling, optimizing Django ORM queries, enhancing FastAPI throughput, refining PostgreSQL indexing, tuning MongoDB execution plans, scaling Kafka clusters on AWS, and guiding scalable microservices design as a Senior Python Engineer.
• Knowledge of distributed reliability engineering within regulated healthcare and telecom infrastructures, including fault tolerance design, horizontal scaling, load balancing strategies, PostgreSQL replication, MongoDB clustering, Kafka consumer management, and multi-region AWS high-availability and GCP auto-scaling solutions.
• Experience collaborating with cross-functional teams as a Senior Python Engineer, mentoring engineers in Django best practices, FastAPI scalability, PostgreSQL tuning, MongoDB schema optimization, Kafka configuration, and AWS and GCP architectural patterns.
• Expertise in event-driven system architecture using Python integrated with Kafka streams, Redis distributed caching, asynchronous FastAPI processing, and resilient Docker-Kubernetes deployments across AWS and GCP supporting mission-critical healthcare systems.
• Knowledge of scalable CI/CD frameworks for Python ecosystems within healthcare and telecom enterprises, incorporating automated testing suites, container build strategies, Kubernetes rollout automation, Terraform state governance, and secure cloud deployment controls.
• Experience leading full-stack engineering initiatives across hospitals, telecom, and enterprise technology domains, leveraging Python, Django, React, Node.js, and TypeScript, delivering RESTful and GraphQL APIs, optimizing PostgreSQL and MongoDB workloads, enabling Kafka-driven event ecosystems, and automating CI/CD pipelines.
• Proficiency in implementing secure authentication and authorization within Django using Core Python, encrypting SQL datasets, securing MongoDB clusters, and configuring GCP IAM policies while enhancing backend performance through optimized Python algorithms.
• Expertise in data engineering frameworks leveraging Python and Airflow orchestration, integrating Databricks analytics, Snowflake warehousing, Kafka ingestion pipelines, PostgreSQL transactional engines, and containerized AWS and GCP infrastructure to deliver enterprise-grade data platforms.
• Experience in developing highly available APIs with Python, FastAPI, and Django for healthcare systems, enabling asynchronous processing, Redis caching optimization, PostgreSQL tuning, MongoDB aggregation pipelines, integrating third-party healthcare and enterprise APIs, persisting transactional data across SQL and MongoDB systems, and configuring secure GCP VPC networking to ensure backend resilience.
• Knowledge of scalable data modeling across PostgreSQL relational schemas and MongoDB document collections for healthcare records and telecom datasets, implementing SQL replication, configuring MongoDB sharding, applying Snowflake warehousing standards, and enabling Databricks ETL transformations powered by Python in AWS-native ecosystems.
• Expertise serving as Senior Python Engineer guiding architectural strategy across healthcare and telecom systems, enforcing scalable microservices design, optimizing MongoDB data layers, integrating Kafka event streaming, managing Snowflake and Databricks data platforms.
• Proficiency in implementing clean architecture principles in Python, enforcing SOLID standards, microservices segregation, API gateway governance, Docker standards, Kubernetes orchestration, Terraform automation, and AWS and GCP compliance frameworks.
• PostgreSQL replication, MongoDB clustering, Kafka consumer management, and multi-region AWS high-availability solutions.
• Proficiency in crafting optimized Core Python automation scripts, administering SQL migrations in Django, designing MongoDB indexing frameworks, and deploying applications via GCP Cloud Build pipelines while refining backend throughput.
• Expertise in advanced data modeling using SQL and MongoDB, developing reusable Core Python components, structuring Django middleware layers, and deploying containerized microservices within GCP infrastructures while strengthening backend efficiency.
• Experience integrating third-party healthcare and enterprise APIs into Django applications powered by Core Python, persisting transactional data across SQL and MongoDB systems, and configuring networking within GCP VPC infrastructures to ensure backend resilience.
• Knowledge of scalable data modeling across PostgreSQL schemas and MongoDB document collections for healthcare records and telecom datasets, applying Snowflake warehousing standards and Databricks ETL transformations powered by Python in AWS-native ecosystems.
• Expertise in backend system architecture using Core Python and Django, implementing advanced SQL analytical queries, modeling MongoDB document structures, and managing secure GCP deployments to elevate backend performance.