Data Engineer

y Responsibilities: 
 

• Design, develop, and optimize Snowflake data warehouse solutions for performance, scalability, and reliability. 
   
• Write complex SQL queries, stored procedures, and scripts to support data transformation and reporting needs. 
   
• Implement ETL/ELT processes using tools such as DBT, Airflow, and Python. 
   
• Monitor and troubleshoot data pipelines, ensuring high availability and minimal downtime. 
   
• Apply best practices for data security, compliance, and governance within Snowflake environments 
  
   

Requirements: 
 

• 4–10 years of professional experience in data engineering or related fields. 
   
• Strong proficiency in SQL and experience with stored procedures. 
   
• Hands-on expertise with Snowflake architecture, performance tuning, and cost optimization. 
   
• Experience with orchestration tools like Apache Airflow. 
   
• Proficiency in DBT for data transformation and modeling. 
   
• Strong programming skills in Python. 
   
• Solid understanding of ETL processes and data integration techniques. 
   
• Experience in working with large datasets and cloud-based data solutions. 
  
   

Soft Skills: 
 

• Strong problem-solving and analytical abilities. 
   
• Excellent communication and collaboration skills. 
   
• Ability to work independently and in a team-oriented environment. 
  
   

Desired Skills and Experience

6 years+ of being a practitioner in data engineering or a related field.

Proficiency in programming skills in Python

Experience with data processing frameworks like Apache Spark or Hadoop.

Experience working on Snowflake and Databricks.

Familiarity with cloud platforms (AWS, Azure) and their data services.

Experience with data warehousing concepts and technologies.

Experience with message queues and streaming platforms (e.g., Kafka)..

Excellent communication and collaboration skills.

Ability to work independently and as part of a geographically distributed team