Key Responsibilities

Design, build, and maintain scalable ETL/ELT pipelines using Snowflake and cloud technologies.
Develop and optimize Snowflake database structures such as warehouses, schemas, tables, streams, tasks, and secure data sharing.
Implement data ingestion from various sources using tools such as ADF, dbt, Kafka, or equivalent.
Write efficient SQL queries and Stored Procedures (Snowflake Scripting / JavaScript UDFs).
Implement best practices including data quality, data validation, and governance standards.
Work closely with Data Architects, Analysts, and BI teams to support reporting and analytical requirements.
Troubleshoot performance issues and apply Snowflake performance optimizations like micro-partitioning, clustering, and caching.
Manage secure access controls and data sharing following security/compliance policies.
Participate in CI/CD and DevOps for data workloads using Git, Terraform, etc.
Support workload migration from legacy systems to Snowflake.

Required Skills

5+ Years of experience as a Data Engineer or similar role.
Strong hands-on experience with Snowflake, including:
- Snowflake architecture & features (compute/storage)
- Virtual warehouses & resource optimization
- Streams, Tasks, Time Travel & Zero Copy Cloning
Strong SQL expertise with large datasets.
Experience with cloud platforms: Azure / AWS / GCP (any one mandatory).
Expertise in ETL/ELT tools (ADF, dbt, Informatica, Talend, etc.).
Strong knowledge of Python or Scala for data processing.
Familiarity with CI/CD: Git, Azure DevOps, Jenkins, Terraform, etc.
Experience working with structured and semi-structured data (JSON, Parquet).

Preferred Skills

Skillset:

MS SQL

Number Of Open Position:

Snowflake Data Engineer