Please find the JD:
As our Python Expert, you will be the primary subject matter authority on all aspects of Python-based solutions. You will apply your extensive technical knowledge to design, develop, and mentor on advanced automation solutions. Significant experience with configuration management tools like Ansible and Terraform, and a strong foundation in Linux, containerization, and the Elastic stack. This role will play a critical part in shaping our automation strategy, particularly in developing robust, high-performance API integrations and driving the future integration with ServiceNow for comprehensive workflow automation.
Key Responsibilities:
- Strategic Architecture Design: Apply your Python expertise to lead the conceptualization and architecture of scalable, efficient, and resilient infrastructure automation solutions, with a focus on asynchronous and event-driven patterns.
- DevOps Practices Implementation: Champion the implementation of DevOps practices and Python-centric CI/CD pipelines to enhance automation workflows.
- Infrastructure Automation Expertise: Leverage expert-level Python skills to develop intricate automation solutions for network, firewalls, and other IT infrastructure components, focusing on advanced API integrations following RESTful and gRPC principles.
- Technical Mentorship: Act as the lead Python authority, mentoring and providing expert technical guidance to the development team, fostering a culture of continuous improvement and innovation in Python development.
- Container Management Leadership: Offer strategic guidance and establish best practices for container management with Docker and Kubernetes, particularly in Python-based applications.
- Comprehensive Documentation: Create and sustain detailed documentation for Python code, system architecture, and implementation processes.
- Cross-Functional Systems Integration: Collaborate with cross-functional teams to ensure seamless integration with existing systems, including the Elastic software stack and ServiceNow.
- ServiceNow Integration Strategy: Drive the strategic integration of Python-based automation tools with ServiceNow, ensuring alignment with business processes and requirements.
Expert-Level
- Python Libraries & Frameworks: Proven, hands-on experience with a broad range of technologies essential for high-performance data operations and API development, including:
- Data Modeling & ORMs/ODMs (MongoDB Focus): Deep, practical knowledge of PyMongo for direct MongoDB interaction. Extensive experience with MongoEngine and/or Pydantic with MongoDB integration for robust data modeling, validation, and schema enforcement within a NoSQL context. Understanding of best practices for embedding and linking documents.
- Web & API Frameworks: Proficiency in building high-performance, scalable, and secure RESTful and/or GraphQL APIs using FastAPI (highly preferred for modern async APIs), Flask (for lightweight services), and/or Django REST Framework (for comprehensive web applications with ORM capabilities). Strong experience with the Requests library for client-side integration and API consumption.
Optional Skills to Have:
- RPC Frameworks & Protocols: Hands-on experience designing and implementing services using gRPC for efficient inter-service communication.
- Data Handling & Transformation: Expert-level proficiency with Pandas for data manipulation and analysis. Strong experience with PyYAML, lxml, and native JSON handling for configuration and data interchange. Understanding of data serialization/deserialization best practices.
- Task Queues & Concurrency: Celery for distributed task processing and background jobs. Experience with message brokers like RabbitMQ or Redis.
- Testing Frameworks & Methodologies: Pytest (with fixtures, parametrization, and async testing capabilities), Unittest, and Mock for comprehensive unit, integration, and end-to-end testing. Adherence to Test-Driven Development (TDD) principles.
Strong Experience with:
- API Design Principles & Best Practices: Deep understanding of RESTful API design principles, HATEOAS, versioning strategies, error handling, and documentation (e.g., OpenAPI/Swagger).
- Security Best Practices (API & MongoDB): Implementation of API security measures (e.g., OAuth2, JWT, API Keys, rate limiting), and MongoDB security (authentication, authorization with roles, TLS/SSL, encryption at rest, field-level encryption, audit logging).
- Containerization & Orchestration: Docker for containerizing Python applications and MongoDB instances. Familiarity with Kubernetes for deployment and orchestration.
- Infrastructure as Code & Cloud Platforms: Boto3 (for AWS services), python-terraform (for programmatic Terraform interactions). Experience with deploying and managing MongoDB on cloud platforms (e.g., AWS DocumentDB, MongoDB Atlas, Azure Cosmos DB for MongoDB).
- Version Control: Git (GitHub, GitLab, Bitbucket) for collaborative development and code management.
- CI/CD Pipelines: Experience in setting up and maintaining Continuous Integration and Continuous Delivery pipelines using tools like Jenkins, GitLab CI/CD, GitHub Actions, or CircleCI for automated testing, building, and deployment.
- Configuration Management: Ansible and Terraform for automating infrastructure provisioning and application deployment.
- Monitoring & Logging: Tools like Prometheus, Grafana, ELK stack (Elasticsearch, Logstash, Kibana) for application and database monitoring, logging, and alerting.
Requirements
Required Skills and Qualifications:
- MongoDB Database Expertise:
- Schema Design & Optimization: Expert-level understanding of MongoDB's flexible schema model. Ability to design efficient and scalable document schemas for various application needs, including considerations for embedding, referencing, and denormalization.
- Query Optimization & Indexing: Advanced knowledge of query optimization techniques, including effective use of indexes (single-field, compound, multi-key, text, geospatial), $explain command analysis, and performance monitoring.
- Replication & High Availability: Deep understanding and hands-on experience with MongoDB replica sets for data redundancy and high availability, including primary-secondary architecture, elections, and write concerns.
- Sharding & Horizontal Scaling: Practical experience with MongoDB sharding for horizontal scaling of large datasets, including sharding strategies, shard key selection, and balancing.
- Aggregation Framework: Master proficiency in the MongoDB Aggregation Framework for complex data transformations, reporting, and analytics.
- Database Administration & Monitoring (DevOps Context): Familiarity with mongod administration, mongosh utilities, currentOp for active operations, storage monitoring, and common alerts. Understanding of MongoDB Atlas or self-hosted administration best practices.
Benefits
Talent worx is an emerging recruitment consulting and services firm, we are hiring for our client whichis an American multinational information technology company based in Spring, Texas. It is a business-focused organization which works in servers, storage, networking, containerization software and consulting and support. HPE was ranked No. 107 in the 2018 Fortune 500 list of the largest United States corporations by total revenue
