Data Engineer _ML Operations

EXL

6 years

0 Lacs

Gurugram Haryana India

Posted:3 days ago| Platform:

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Skills Required

data ml analytics engineering learning openapi design collaboration etl model training deployment monitoring devops containerization code ai support communication governance compliance security sql python pipeline orchestration airflow processing spark mlflow sagemaker vertex jenkins github gitlab docker kubernetes aws azure kafka

Work Mode

On-site

Job Type

Full Time

Job Description

Analytics & Data Engineering professional

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

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.

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