Job Descriptions

Location: Mumbai

Key Responsibilities:
• Design, build, and maintain scalable and effective data pipelines to support analytics and machine learning model development.
• Develop and optimize data models for structured and unstructured data to ensure high performance and reliability.
• Implement CI/CD pipelines for data workflows and model deployment, ensuring seamless integration and delivery.
• Containerize data engineering and ML workflows using Docker for consistent and reproducible environments.
• Collaborate with data scientists, analysts, and business stakeholders to understand data requirements and deliver high-quality solutions.
• Manage and monitor ML Ops processes including model versioning, deployment, and performance tracking.
• Leverage Azure cloud services (e.g., Azure Data Factory, Azure Synapse, Azure ML, Azure DevOps) to build and manage cloud-native data solutions.
• Ensure data quality, governance, and security across all engineering workflows.




• Document data engineering processes, architecture, and best practices.
• Mentor junior engineers and contribute to a culture of technical excellence and continuous improvement.

Qualifications/Experience:
• Proficiency in Python and SQL; experience with data processing frameworks like Spark is a plus.
• Hands-on experience with Docker, CI/CD tools (e.g., GitHub Actions, Azure DevOps), and ML Ops practices.
• Strong knowledge of Azure cloud platform and its data services.
• Experience with data modeling, ETL/ELT processes, and orchestration tools.
• Familiarity with machine learning workflows and deployment strategies.
• Excellent problem-solving, communication, and collaboration skills.

Competencies

Functional/ Technical Skills*

Interpersonal/ Communication Skills*

Professional Impression*

Relevant Background/Special Skill Set*

📌 Data Engineer (India)
🏢 Recognized
📍 India