DataOrb Python Developer Distributed Systems

Job description

<p>About DataOrb :</p><p><br/></p><p>DataOrb is revolutionizing how organizations understand and utilize their customer data.<br/><br/> We enable businesses of all sizes-from ambitious startups to Fortune 500 companies-to unlock insights from their customer interactions across conversational, transactional, and structured datasets.<br/><br/> Founded by veterans from Google, Amazon, Microsoft, and Samsung, we're driven by a shared mission to democratize customer intelligence and make AI accessible to everyone.<br/><br/>The Opportunity :<br/><br/>We are seeking an experienced Python Developer proficient in object-oriented programming, Python development, cloud technologies, database design, and advanced Python concepts.<br/><br/> The ideal candidate will have a foundational understanding of machine learning, with a strong willingness to learn and grow in this domain.<br/><br/> The role involves writing high-quality Python code following SOLID principles and design patterns, as well as guiding and training team members to elevate their coding standards.<br/><br/>Core Responsibilities :<br/><br/>- Architect and develop robust, scalable, and maintainable Python applications following microservice architecture principles<br/><br/>- Demonstrate proficiency in writing multithreaded and parallel processing code for optimizing performance<br/><br/>- Drive the creation of modularized codebase, ensuring reusability and maintainability across projects<br/><br/>- Develop high-quality Python code adhering to SOLID principles and design patterns<br/><br/>- Design and implement scalable solutions leveraging cloud technologies<br/><br/>- Contribute to database design and optimization strategies<br/><br/>- Mentor and guide team members to enhance code quality and best practices<br/><br/>- Collaborate with cross-functional teams to deliver robust and efficient solutions.<br/><br/>- Collaborate closely with stakeholders to understand requirements and translate them into technical solutions<br/><br/>- Drive code reviews and ensure adherence to coding standards, quality, and performance benchmarks<br/><br/>- Research and implement emerging technologies to enhance system efficiency<br/><br/>- Lead initiatives to improve development processes and tools, fostering innovation and productivity<br/><br/>- Foster a culture of continuous learning and improvement within the team<br/><br/>Required Qualifications :<br/><br/>- Full-time hands-on software engineering experience : Minimum 5+ years designing, developing, and delivering high-performance, production-grade applications using Python in complex, distributed systems.<br/><br/>- Expert-level proficiency in Python 3.12+ (or latest stable release)<br/><br/>- Deep understanding of object-oriented programming (OOP), design patterns (e., Singleton, Factory, Strategy), and Python-specific idioms (e.

, context managers, decorators, generators, async/await).<br/><br/>- Follows PEP8 standards and best practices for readable, maintainable, and testable code.<br/><br/>- Proficient in type hints (PEP 484), dataclasses, and pydantic for robust, type-safe applications.<br/><br/>- Strong grasp of core engineering concepts :<br/><br/>1.

Connection pooling (e.

, SQLAlchemy, psycopg2 connection pools)<br/><br/>2.

Scalability, throughput optimization, memory management, and profiling using tools like cProfile, line_profiler, memory_profiler.<br/><br/>- Asynchronous programming using asyncio, aiohttp, and event-driven architectures.<br/><br/>- Experience designing distributed systems and microservices using REST APIs, gRPC, or GraphQL.<br/><br/>- Cloud-native development experience, preferably with AWS (Lambda, SQS, SNS, S3, RDS, DynamoDB, SageMaker).<br/><br/>- Strong database expertise :<br/><br/>1.

Relational databases (PostgreSQL, MySQL) : query optimization, indexing strategies, schema design, transactions.<br/><br/>2.

NoSQL databases (MongoDB 7+, DynamoDB) : data modeling, query optimization, partitioning strategies.<br/><br/>- Proficient in testing methodologies :<br/><br/>1.

Unit testing (pytest, unittest), integration testing, mocking (unittest mock, pytest-mock), and Test-Driven Development (TDD) practices.<br/><br/>- Familiarity with Testcontainers for integration tests in containerized environments.<br/><br/>- Containerization and orchestration :<br/><br/>1.

Proficiency with Docker (latest best practices, multi-stage builds, slim images).<br/><br/>2.

Experience with Kubernetes : deployments, services, config maps, secrets, and Helm charts.<br/><br/>3.

Experience guiding and mentoring team members-code reviews, knowledge sharing, and promoting best practices across teams.<br/><br/>- Excellent communication and collaboration skills-able to articulate design choices, trade-offs, and complex technical topics to both technical and non-technical stakeholders.<br/><br/>- Exposure to Machine Learning concepts :<br/><br/>- Familiarity with ML frameworks: TensorFlow 2.x, PyTorch 2.x, scikit-learn, or XGBoost.<br/><br/>- Experience integrating models into production services (model serving, feature stores, API wrappers).<br/><br/>- Hands-on experience with MLOps pipelines and tools<br/><br/>- AWS SageMaker for model training, deployment, and monitoring.<br/><br/>- MLflow, Kubeflow, or ZenML for experiment tracking and reproducibility.<br/><br/>- Bonus : Experience with API design principles (OpenAPI/Swagger) and CI/CD pipelines for Python applications (GitHub Actions, GitLab CI, or Jenkins).<br/><br/>- Experience using Cloud ML platforms and MLOps frameworks in production environments, preferably AWS SageMaker<br/><br/>Desired Experience :<br/><br/>- Background in working on SaaS products<br/><br/>- Experience with AI/ML products<br/><br/>- Enterprise Python Engineer experience<br/><br/>Educational Requirements :<br/><br/>Bachelor's Or Master's degree in one of the following fields :<br/><br/>- Bachelor of Computer Science<br/><br/>- Bachelor of Engineering (Information Technology)<br/><br/>- Masters of Computer Science<br/><br/>- Master of Engineering (Information professional experience in Python Engineer (typically 4+ additional years of hands-on experience beyond the base requirement)<br/><br/>Technical Toolkit :<br/><br/>- Python<br/><br/>- Django<br/><br/>- MongoDB<br/><br/>- Multithreading<br/><br/>- AWS<br/><br/>Why Join DataOrb :<br/><br/>- Mission : Be part of democratizing customer intelligence and making AI accessible<br/><br/>- Impact : Shape how organizations understand and serve their customers<br/><br/>- Team : Work with experienced leaders from top tech companies<br/><br/>- Growth : Rapid scaling environment with significant learning opportunities<br/><br/>- Culture : Autonomous, trust-based environment focused on outcomes<br/><br/></p><p>Benefits :<br/><br/>- Flexible work arrangements<br/><br/>- Comprehensive health coverage<br/><br/>- Generous PTO policy<br/><br/>- Professional development support<br/><br/>- Competitive compensation package<br/><br/>Our Values :<br/><br/>- Customer Obsession : We practice what we preach<br/><br/>- Democratizing Technology : Making complex solutions accessible<br/><br/>- Innovation with Purpose : Solving real customer problems<br/><br/>- Trust and Autonomy : Freedom to create and deliver excellence</p> (ref:hirist.tech)

Required Skill Profession

Computer Occupations