We are seeking a highly skilled and innovative Software Engineer with Data Science knowledge to join our dynamic team. The ideal candidate will have a strong background in both software/data engineering and knowledge of data science is preferable. This role will involve developing and maintaining software applications, building and optimizing scalable data pipelines, and implementing data science/ AI solutions to enhance our marketing strategies and customer experiences.
Key Responsibilities:
- Implement full software development process (React preferred)
- Work with data streams and APIs to provide enhanced automation capabilities.
- Develop flowcharts, layouts, and documentation to identify requirements and solutions.
- Gather user requirements and technical requirements.
- Write well-designed, testable code.
- Automate and scale data pipelines with data engineers to support marketing analytics.
- Implement generative AI solutions to enhance marketing workflows. Stay current with AI/ML advancements and prototype innovative solutions.
- Collaborate with cross-functional teams to gather requirements and translate them into technical specifications.
- Ensure compliance with data privacy regulations and implement best practices in data management and governance.
Requirements:
- Min 5+ years of experience with Bachelor's degree in Computer Science, Data Science, or a related STEM field. knowledge of using agile software development techniques. Excellent interpersonal skills and an eagerness to collaborate.
- Frontend Technologies: Proficiency in HTML, CSS, and JavaScript, along with frameworks like React or Angular.
- Backend Technologies: Strong knowledge of Node.js, Python, or Java, and experience with backend frameworks such as Express.js or Django.
- Docker: Experience with Docker for containerization, including creating and managing Docker containers, Docker Compose, and Docker Swarm.
- Database Management: Proficiency in SQL (knowledge of NoSQL databases is advantage) and experience with data warehousing solutions such as Azure Synapse Analytics2.
- Cloud Platforms: Knowledge of Azure Databricks cloud services preferred, specifically services related to data storage, processing, and deployment.
- Version Control: Proficiency in using Git and GitHub for version control and collaboration.
Good to have-
- Familiarity with ML frameworks (scikit-learn, TensorFlow, PyTorch) and MLOps practices.
- Knowledge of large language models (LLMs) and generative AI technologies.
- DevOps: Understanding of CI/CD pipelines, and experience with tools like Jenkins, GitLab CI, or Azure DevOps.