Senior Data Engineer / MLOps Engineer
Position Summary
Design, build, and optimize scalable data platforms, machine learning infrastructure, and AI-powered applications that support advanced analytics and business decision-making. Lead development efforts across data engineering, MLOps, cloud-native services, and AI/LLM solutions while ensuring reliability, scalability, and operational excellence. Atul's work includes Snowflake migrations, feature engineering, ML pipeline development, AI application enablement, and production support.
Key Responsibilities
Design and develop data pipelines and ETL/ELT solutions using modern cloud and data engineering practices.
Build and maintain MLOps workflows, feature stores, feature snapshot services, model pipelines, and production ML infrastructure.
Develop AI-enabled applications and LLM-powered solutions, integrating enterprise data sources into production-ready systems.
Create and manage microservices and scheduled applications within cloud ecosystems to support analytics and machine learning workloads.
Implement monitoring, alerting, performance testing, and operational controls using tools such as Grafana and related observability platforms.
Collaborate with data scientists, analytics teams, and business stakeholders to translate requirements into scalable technical solutions.
Support cloud data platform modernization efforts, including migration initiatives from legacy databases to Snowflake and other modern architectures.
Troubleshoot production issues, optimize data processing performance, and ensure solution reliability at scale.
Preferred Technical Skills
Data Engineering and Data Warehousing
Snowflake
SQL and Data Modeling
Python
MLOps and Machine Learning Pipelines
Feature Stores and Feature Engineering
AI/LLM Application Development
Cloud-Native Microservices
API Development and Integration
Redis
Grafana Monitoring and Alerting
DevOps and CI/CD Practices
Production Performance Optimization
Analytics Engineering
Soft Skills
Strong problem-solving and troubleshooting abilities
Ability to work independently with minimal oversight
Excellent collaboration across engineering, data science, and business teams
Effective communication of complex technical concepts to non-technical audiences
Adaptability across multiple concurrent projects and priorities
Continuous improvement mindset focused on scalability and operational efficiency

Data MLOPS Engineer

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