Snowflake Data Engineer

Roles & Responsibilities:

• Design, develop, and optimize scalable

  ETL/ELT pipelines

  using

  Snowflake

  ,

  AWS Glue

  , and

  dbt (Data Build Tool)

  .
• Build and maintain robust

  data models

  (star/snowflake schema) to support business intelligence and analytics use cases.
• Use

  PySpark

  and

  SQL

  for data processing, transformation, and querying large-scale datasets efficiently.
• Integrate data from various sources using

  AWS Lambda

  , APIs, and event-driven architecture where needed.
• Monitor and manage data pipeline performance, reliability, and cost-efficiency on the

  AWS cloud

  platform.
• Collaborate with data analysts, product managers, and other stakeholders to gather requirements and implement technical solutions.
  
• Ensure data quality, data governance, and compliance throughout the data lifecycle.
  
• Implement CI/CD practices for data workflows and ensure version control using tools like Git.
  

Technical Requirements:

• Strong experience in

  Snowflake

  development and performance tuning.
• Hands-on with

  AWS services

  especially

  AWS Glue

  ,

  S3

  ,

  Lambda

  , and

  CloudWatch

  .
• Proficient in

  SQL

  , with experience writing complex queries and optimizing them.
• Working knowledge of

  PySpark

  for distributed data processing.
• Proficiency with

  dbt

  (Data Build Tool) for transformation layer and data modeling.
• Solid understanding of

  ETL/ELT processes

  , data warehousing concepts, and

  data modeling

  .
• Experience working in an Agile development environment with tools like JIRA or Azure DevOps.