Data Engineer - Snowflake DB

Job Summary

Key Responsibilities

• Build scalable and efficient Snowflake pipelines for data ingestion, transformation, and storage.
• Special focus on external tables, semi-structured data handling, and transformation logic.
  

Optimize Snowflake Workloads

• Ensure optimal query execution and cost-effective utilization of compute and storage resources.
• Tune performance across large-scale datasets and implement workload management strategies.
  

ETL/ELT Development

• Develop robust ETL processes using SQL, Python, and orchestration tools like DBT, Apache Airflow, Matillion, or Talend.
• Focus on automation, data transformation, and pipeline reliability.
  

Integrate With AWS Glue

• Utilize AWS Glue capabilities such as crawlers, jobs, and external tables for seamless integration with Snowflake.
• Ensure consistent and automated data ingestion and cataloging.
  

Data Governance & Security

• Enforce data governance, role-based access control, and compliance protocols within Snowflake.
• Ensure secure handling of sensitive data and privacy adherence.
  

Handle Diverse Data Formats

• Ingest and transform structured and semi-structured formats like JSON, Parquet, Avro, XML, etc.
• Enable flexibility in data consumption across reporting and analytics.
  

Data Modeling

• Design dimensional models including fact and dimension tables optimized for Snowflake architecture.
• Enable efficient querying and integration with BI tools.
  

Cross-Functional Collaboration

• Partner with business stakeholders, data analysts, and BI developers to align technical solutions with business needs.
• Translate business requirements into scalable data solutions.
  

Pipeline Monitoring & Issue Resolution

• Monitor end-to-end data workflows and ensure system reliability.
• Troubleshoot failures and performance bottlenecks proactively.
  

Key Skills & Qualifications

• Hands-on experience with Snowflake development and architecture.
• Proficiency in SQL, Python, and cloud-native ETL/ELT tools.
• Experience with AWS Glue, S3, and Snowflake integration.
• Strong knowledge of data modeling, performance tuning, and cost optimization.
• Familiarity with handling semi-structured data.
• Good understanding of data governance, access control, and security best practices.
• Excellent problem-solving and communication skills.
  

Nice To Have

• Experience working with Big 4 consulting clients or large enterprise environments.
• Exposure to DevOps practices, CI/CD pipelines, and data quality framework