DL
Morgan Stanley: Senior Snowflake Data Engineer
Diverse Lynx India
Location not stated
Senior
1 month ago
- Snowflake
- ETL
- ELT
- Data Modeling
- Python
- SQL
- Cortex
- AI
- Data Architecture
- Vault
- AI/ML
- JSON
- XML
- Parquet
- Apache Avro
- RBAC
- Devops
- AWS
- Azure
- GCP
- CI/CD
- Git
- Jenkins
- Azure DevOps
- IaC
- Machine Learning
- RAG
1 month ago
## Role Overview
We are seeking a highly skilled **Snowflake Data Engineer** with 6–8 years of experience in Data Engineering, Cloud Data Platforms, and Data Warehousing. The ideal candidate should possess strong expertise in designing scalable data architectures, implementing robust ETL/ELT frameworks, developing performant Snowflake solutions, and integrating enterprise data from multiple sources including APIs, databases, and semi-structured data formats.
The candidate should have hands-on experience in **Snowflake Security & Governance, Data Modeling, Performance Optimization, Python-based Data Engineering, and Advanced SQL Development**. Experience with **Snowflake Cortex and AI-driven data solutions** is highly desirable.
# Key Responsibilities
### Snowflake Data Engineering
- Design, build, and maintain scalable data pipelines on Snowflake.
- Develop and optimize Snowflake databases, schemas, warehouses, and storage strategies.
- Implement data ingestion frameworks using batch and near real-time processing techniques.
- Build solutions leveraging Snowpipe, Streams, Tasks, Stored Procedures, and Dynamic Tables.
- Optimize Snowflake workloads for performance, scalability, and cost efficiency.
### Data Architecture & Modeling
- Design enterprise-grade data warehouse solutions using dimensional modeling techniques.
- Develop Star Schema, Snowflake Schema, and Data Vault models based on business requirements.
- Create scalable data architectures supporting analytics, reporting, and AI/ML workloads.
- Define data transformation and orchestration frameworks.
### Data Integration & APIs
- Develop and maintain API-based data ingestion solutions.
- Integrate Snowflake with enterprise applications and cloud platforms.
- Process structured and semi-structured data including JSON, XML, Parquet, Avro, and CSV formats.
- Implement robust error handling, auditing, and reconciliation frameworks.
### Security, Governance & Compliance
- Implement Snowflake RBAC and access management frameworks.
- Configure roles, privileges, masking policies, row access policies, and secure views.
- Ensure compliance with enterprise security and regulatory requirements.
- Establish data governance and monitoring standards.
### Cloud & DevOps
- Integrate Snowflake with AWS, Azure, or GCP ecosystems.
- Support CI/CD automation using Git, Jenkins, Azure DevOps, or similar tools.
- Implement Infrastructure-as-Code and deployment automation strategies.
### AI & Snowflake Cortex
- Build data solutions leveraging Snowflake Cortex capabilities.
- Develop use cases involving document processing, semantic search, embeddings, and GenAI integrations.
- Support AI-ready data architecture and Retrieval-Augmented Generation (RAG) use cases.
Morgan Stanley: Senior Snowflake Data Engineer · Diverse Lynx India