Job Title: Associate – Business Analyst (Data Engineering / Cloud Data Engineering)
Experience: 0–3 years
Location: Noida (Hybrid)
Salary: 5–8 LPA
Job Role:
Data Engineering – Cloud Data Engineering
Job Description:
We are seeking a highly motivated Associate – Business Analyst with strong Data Engineering and Cloud Data Engineering capabilities. The ideal candidate should have solid hands-on programming experience in Python, including familiarity with design patterns, and strong skills in Kubernetes and Docker for building and optimizing containerized applications. Experience working on Azure or Google Cloud Platform, along with machine learning services and industry best practices, is essential. You must possess strong problem-solving skills, a willingness to dive deep into technical challenges, and the ability to propose effective solutions. The role also requires multitasking and prioritizing responsibilities across multiple projects.
Responsibilities:
- Collaborate closely with data scientists to troubleshoot ML model execution challenges and recommend effective solution architectures.
- Work with MLOps tools across the ML lifecycle, including feature stores (e.g., FEAST), model registries, problem optimizers (e.g., GUROBI), and real-time model serving frameworks.
- Support the deployment, monitoring, and optimization of machine learning workflows.
- Develop and optimize containerized ML and data pipelines using Kubernetes and Docker.
- Ensure cloud best practices are followed across Azure or GCP deployments.
Preferred Certifications:
- CKA – Certified Kubernetes Administrator
- CKAD – Certified Kubernetes Application Developer
Required Skills & Knowledge:
- Strong hands-on programming experience in Python with design patterns.
- Hands-on expertise in Kubernetes and Docker.
- Familiarity with Azure or GCP cloud platforms.
- Strong SQL skills.
- Understanding of ML platforms such as Kubeflow and Vertex AI.
- Knowledge of ML frameworks including XGBoost, PyTorch, and TensorFlow.
Qualifications:
- 0–3 years of experience in Data Engineering, Cloud Data Engineering, or MLOps.
- Experience supporting data scientists with ML model execution challenges.
- Experience using MLOps tools including FEAST, GUROBI, model registries, or real-time serving platforms.