Data MLOPS Engineer
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 SkillsData Engineering and Data Warehousing
- SnowflakeSQL and Data Modeling
- PythonMLOps and Machine Learning Pipelines
- Feature Stores and Feature EngineeringAI/LLM Application Development
- Cloud-Native MicroservicesAPI Development and Integration
- RedisGrafana Monitoring and Alerting
- DevOps and CI/CD Practices
- Production Performance Optimization
- Analytics Engineering
- Soft SkillsStrong 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