Etl Developer

Role Overview:

ETL Developer

This role requires hands-on technical expertise, problem-solving skills, and the ability to collaborate with cross-functional teams to deliver scalable and efficient data solutions.

Key Responsibilities:

• ETL Development & Data Integration:

• Design, develop, and optimize ETL pipelines using

  Snowflake

  and

  dbt (Data Build Tool)

  .
  
• Implement transformations using

  Jinja templates

  and

  SQL models

  in dbt.
  
• Ensure data is cleansed, validated, and transformed accurately to meet business requirements.
  

• Data Modeling & Architecture:

• Work with stakeholders to design and implement

  star schema / snowflake schema

  and other optimized data models.
  
• Support data warehousing initiatives and ensure alignment with data architecture best practices.
  

• Performance Optimization:

• Monitor, troubleshoot, and optimize SQL queries, dbt models, and Snowflake pipelines for better efficiency.
  
• Implement best practices for performance tuning, query optimization, and cost management in Snowflake.
  

• Automation & Scripting:

• Leverage

  Python

  for automating ETL workflows, data quality checks, and operational tasks.
  
• Integrate dbt with orchestration frameworks (e.g., Airflow, dbt Cloud, or equivalent).
  

• Data Governance & Quality:

• Implement data validation frameworks, audit checks, and reconciliation processes.
  
• Maintain documentation of ETL workflows, data models, and transformations for transparency and governance.
  

• Collaboration & Support:

• Partner with business analysts, data scientists, and BI developers to provide high-quality, reliable datasets.
  
• Provide production support for ETL jobs, ensuring timely resolution of issues.
  

Required Skills (Mandatory):

• Snowflake:

• Advanced knowledge of Snowflake features (Warehouses, Schemas, Cloning, Micro-partitioning, Streams, Tasks).
  
• Experience in query optimization, performance tuning, and cost-effective scaling in Snowflake.
  

• dbt (Data Build Tool):

• Strong experience in developing and maintaining dbt models.
  
• Proficiency in

  Jinja templating

  and

  SQL transformations

  in dbt.
  
• Knowledge of dbt testing frameworks and deployment practices.
  

• SQL Expertise:

• Advanced SQL programming skills for data transformation, analysis, and performance optimization.
  

Secondary Skills (Preferred):

• Python:

• Strong scripting and automation capabilities.
  
• Experience in integrating Python scripts into ETL workflows.
  
• Familiarity with data manipulation libraries (e.g., Pandas, PySpark).
  
• Familiarity with cloud platforms (AWS/Azure/GCP) and orchestration tools like

  Airflow

  .
  
• Knowledge of version control (Git/GitHub/GitLab) and CI/CD practices.
  
• Exposure to data visualization tools (Tableau, Power BI) is a plus.