Data Engineer
- Build data pipelines and deploying AI/ML solutions to solve business challenges across different domains.
- Develop end-to-end AI/ML workflows including data ingestion, transformation, deployment, and monitoring
- Design and optimize ETL processes for seamless data integration across cloud and analytics platforms
- Integrate AI/ML models into production systems using APIs and microservices
- Monitor data quality, pipeline performance, and model reliability to ensure scalability and efficiency
- Contribute to data engineering standards, governance practices, and secure data management
- Bachelor’s degree in Computer Science, Data Science, Artificial Intelligence, or a related field
- 2-4 years of experience (either in data or related fields) in AI/ML or data related roles
- Strong proficiency in Python and familiarity with ML libraries (e.g., scikit-learn, TensorFlow, PyTorch) and familiarity with AI frameworks.
- Practical knowledge of data preprocessing, model optimization, and evaluation techniques.
- Experience with cloud platforms (AWS, Azure, or GCP) and containerize on tools (Docker, Kubernetes).
- Understanding of MLOps concepts and version control systems (Git).
- Working experience of SQL/NoSQL databases and data pipeline management tools
- Strong problem-solving mindset and willingness to learn
- Good communication and collaboration skills
- Business analysis
- Hands-on experience working on real-world projects
- Mentorship from senior consultants and technical leads
- Exposure to client-facing consulting environments
- Opportunities to build expertise in emerging AI technologies
- A structured learning and growth path within the organization