Data Engineer

Senior Data Engineer

Key Responsibilities:

• Design and implement robust, scalable, and efficient data pipelines using ETL/ELT frameworks.
  
• Develop and manage data models and data warehouse architecture within

  Snowflake

  .
• Create and maintain

  DBT

  models for transformation, lineage tracking, and documentation.
• Write modular, reusable, and optimized Python scripts for data ingestion, transformation, and automation.
  
• Collaborate closely with data analysts, data scientists, and business teams to gather and fulfill data requirements.
  
• Ensure data integrity, consistency, and governance across all stages of the data lifecycle.
  
• Monitor pipeline performance and implement optimization strategies for queries and storage.
  
• Follow best practices for data engineering including version control (Git), testing, and CI/CD integration.
  

Required Skills and Qualifications:

• 8+ years

  of experience in Data Engineering or related roles.
• Deep expertise in

  Snowflake

  : schema design, performance tuning, security, and access controls.
• Proficiency in

  Python

  , particularly for scripting, data transformation, and workflow automation.
• Strong understanding of

  data modeling

  techniques (e.g., star/snowflake schema, normalization).
• Proven experience with

  DBT

  for building modular, tested, and documented data pipelines.
• Familiarity with ETL/ELT tools and orchestration platforms like

  Apache Airflow

  or

  Prefect

  .
• Advanced

  SQL

  skills with experience handling large and complex data sets.
• Exposure to cloud platforms such as

  AWS

  ,

  Azure

  , or

  GCP

  and their data services.

Preferred Qualifications:

• Experience implementing data quality checks and governance frameworks.
  
• Understanding of modern data stack and CI/CD pipelines for data workflows.
  
• Contributions to data engineering best practices, open-source projects, or thought leadership.