4604092-Senior Manager

EXL Talent Acquisition Team; Gurugram District; Sur place; INR 2 000 000 - 3 600 000; Plein temps

Résumé du poste

EXL Talent Acquisition Team is seeking a seasoned Analytics & Data Engineering professional in India to design and implement scalable ML data pipelines and production-grade systems. You will work closely with data scientists, product teams, and engineers to deliver robust analytics solutions.

The role emphasizes hands-on engineering and solution design, with focus on MLOps, DevOps practices, and agent-based communications using MCP/OpenAPI and A2A protocols.

Qualifications

• Strong experience designing and implementing scalable data pipelines.
• Experience deploying and maintaining ML models in production.
• Proficiency with SQL, Python, and data orchestration tools.

Responsabilités

• Design, build, and maintain scalable data pipelines and ETL/ELT processes for analytics and ML workloads.
• Implement MLOps frameworks to manage model lifecycle (training, deployment, monitoring, retraining).
• Apply DevOps best practices (CI/CD, containerization, infrastructure as code) to ML and data engineering workflows.
• Develop and optimize data models, feature stores, and ML serving architectures.
• Collaborate with AI/ML teams to integrate models into production environments.
• Support agent development using MCP/OpenAPI to MCP wrapper and A2A communication protocols.
• Ensure data quality, governance, and compliance with security best practices.
• Troubleshoot and optimize data workflows for performance and reliability.

Connaissances

SQL

Python

Airflow

Data modeling

MLOps

Docker

Kubernetes

OpenAPI MCP

A2A protocols

Formation

Master's degree in CS / Data Eng

Outils

Spark

Databricks

Cloud (AWS/Azure/GCP)

MLflow

Kubeflow

SageMaker

Vertex AI

Description du poste

We are looking for a highly skilled Analytics & Data Engineering professional with a strong background in Machine Learning, MLOps, and DevOps. The ideal candidate will have experience designing and implementing scalable data and analytics pipelines, enabling production-grade ML systems, and supporting agent-based development leveraging MCP/OpenAPI to MCP wrapper and A2A protocols. This role combines hands-on technical work with solution design, and will require close collaboration with data scientists, product teams, and engineering stakeholders.

Key Responsibilities

• Design, build, and maintain scalable data pipelines and ETL/ELT processes for analytics and ML workloads.
• Implement MLOps frameworks to manage model lifecycle (training, deployment, monitoring, and retraining).
• Apply DevOps best practices (CI/CD, containerization, infrastructure as code) to ML and data engineering workflows.
• Develop and optimize data models, feature stores, and ML serving architectures.
• Collaborate with AI/ML teams to integrate models into production environments.
• Support agent development using MCP/OpenAPI to MCP wrapper and A2A (Agent-to-Agent) communication protocols.
• Ensure data quality, governance, and compliance with security best practices.
• Troubleshoot and optimize data workflows for performance and reliability.

Required Skills & Experience

• Core:6+ years in analytics and data engineering roles.
• Proficiency in SQL, Python, and data pipeline orchestration tools (e.g., Airflow, Prefect).
• Experience with distributed data processing frameworks (e.g., Spark, Databricks).
• ML/MLOps:Experience deploying and maintaining ML models in production.
• Knowledge of MLOps tools (MLflow, Kubeflow, SageMaker, Vertex AI, etc.).
• DevOps:Hands-on experience with CI/CD (Jenkins, GitHub Actions, GitLab CI).
• Proficiency with Docker, Kubernetes, and cloud-based deployment (AWS, Azure, GCP).
• Specialized:Experience with MCP/OpenAPI to MCP wrapper integrations.
• Experience working with A2A protocols in agent development.
• Familiarity with agent-based architectures and multi-agent communication patterns.

Preferred Qualifications

• Master's degree in Computer Science, Data Engineering, or related field.
• Experience in real-time analytics and streaming data pipelines (Kafka, Kinesis, Pub/Sub).
• Exposure to LLM-based systems or intelligent agents.
• Strong problem-solving skills and ability to work in cross-functional teams.