About DataOrb :
DataOrb is revolutionizing how organizations understand and utilize their customer data.
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.
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.
The Opportunity :
We are seeking an experienced Python Developer proficient in object-oriented programming, Python development, cloud technologies, database design, and advanced Python concepts.
The ideal candidate will have a foundational understanding of machine learning, with a strong willingness to learn and grow in this domain.
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.
Core Responsibilities :
- Architect and develop robust, scalable, and maintainable Python applications following microservice architecture principles
- Demonstrate proficiency in writing multithreaded and parallel processing code for optimizing performance
- Drive the creation of modularized codebase, ensuring reusability and maintainability across projects
- Develop high-quality Python code adhering to SOLID principles and design patterns
- Design and implement scalable solutions leveraging cloud technologies
- Contribute to database design and optimization strategies
- Mentor and guide team members to enhance code quality and best practices
- Collaborate with cross-functional teams to deliver robust and efficient solutions.
- Collaborate closely with stakeholders to understand requirements and translate them into technical solutions
- Drive code reviews and ensure adherence to coding standards, quality, and performance benchmarks
- Research and implement emerging technologies to enhance system efficiency
- Lead initiatives to improve development processes and tools, fostering innovation and productivity
- Foster a culture of continuous learning and improvement within the team
Required Qualifications :
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.Expert-level proficiency in Python 3.12+ (or latest stable release)Deep understanding of object-oriented programming (OOP), design patterns (e., Singleton, Factory, Strategy), and Python-specific idioms (e. , context managers, decorators, generators, async / await).Follows PEP8 standards and best practices for readable, maintainable, and testable code.Proficient in type hints (PEP 484), dataclasses, and pydantic for robust, type-safe applications.Strong grasp of core engineering concepts :1. Connection pooling (e. , SQLAlchemy, psycopg2 connection pools)
2. Scalability, throughput optimization, memory management, and profiling using tools like cProfile, line_profiler, memory_profiler.
Asynchronous programming using asyncio, aiohttp, and event-driven architectures.Experience designing distributed systems and microservices using REST APIs, gRPC, or GraphQL.Cloud-native development experience, preferably with AWS (Lambda, SQS, SNS, S3, RDS, DynamoDB, SageMaker).Strong database expertise :1. Relational databases (PostgreSQL, MySQL) : query optimization, indexing strategies, schema design, transactions.
2. NoSQL databases (MongoDB 7+, DynamoDB) : data modeling, query optimization, partitioning strategies.
Proficient in testing methodologies :1. Unit testing (pytest, unittest), integration testing, mocking (unittest mock, pytest-mock), and Test-Driven Development (TDD) practices.
Familiarity with Testcontainers for integration tests in containerized environments.Containerization and orchestration :1. Proficiency with Docker (latest best practices, multi-stage builds, slim images).
2. Experience with Kubernetes : deployments, services, config maps, secrets, and Helm charts.
3. Experience guiding and mentoring team members-code reviews, knowledge sharing, and promoting best practices across teams.
Excellent communication and collaboration skills-able to articulate design choices, trade-offs, and complex technical topics to both technical and non-technical stakeholders.Exposure to Machine Learning concepts :Familiarity with ML frameworks : TensorFlow 2.x, PyTorch 2.x, scikit-learn, or XGBoost.Experience integrating models into production services (model serving, feature stores, API wrappers).Hands-on experience with MLOps pipelines and toolsAWS SageMaker for model training, deployment, and monitoring.MLflow, Kubeflow, or ZenML for experiment tracking and reproducibility.Bonus : Experience with API design principles (OpenAPI / Swagger) and CI / CD pipelines for Python applications (GitHub Actions, GitLab CI, or Jenkins).Experience using Cloud ML platforms and MLOps frameworks in production environments, preferably AWS SageMakerDesired Experience :
Background in working on SaaS productsExperience with AI / ML productsEnterprise Python Engineer experienceEducational Requirements :
Bachelor's Or Master's degree in one of the following fields :
Bachelor of Computer ScienceBachelor of Engineering (Information Technology)Masters of Computer ScienceMaster of Engineering (Information professional experience in Python Engineer (typically 4+ additional years of hands-on experience beyond the base requirement)Technical Toolkit :
PythonDjangoMongoDBMultithreadingAWSWhy Join DataOrb :
Mission : Be part of democratizing customer intelligence and making AI accessibleImpact : Shape how organizations understand and serve their customersTeam : Work with experienced leaders from top tech companiesGrowth : Rapid scaling environment with significant learning opportunitiesCulture : Autonomous, trust-based environment focused on outcomesBenefits :
Flexible work arrangementsComprehensive health coverageGenerous PTO policyProfessional development supportCompetitive compensation packageOur Values :
Customer Obsession : We practice what we preachDemocratizing Technology : Making complex solutions accessibleInnovation with Purpose : Solving real customer problemsTrust and Autonomy : Freedom to create and deliver excellence(ref : hirist.tech)