Data Engineer

Data Engineer

Key Responsibilities

• Design, develop, and maintain scalable ETL/ELT pipelines

  using

  dbt, Snowflake, and Python

  .
• Optimize

  Snowflake data models and warehouse performance

  (partitioning, clustering, caching, query tuning).
• Collaborate with analysts, scientists, and business teams to deliver high-quality curated datasets.
  
• Ensure

  data quality, governance, and compliance

  across all pipelines.
• Automate workflows and monitor production jobs to ensure accuracy and reliability.
  
• Contribute to architectural decisions, advocating

  best practices in data engineering

  .
• Maintain documentation of data pipelines, dbt models, and data architecture.
  
• Mentor junior engineers and support team-wide knowledge sharing.
  

Mandatory Skills & Qualifications

• 3+ years of professional experience

  in Data Engineering.

• Hands-on expertise in Snowflake

  (data modeling, performance tuning, optimization, security features).

• Proven, production-level experience using dbt

  for data transformation, modeling, and testing.
• Strong

  Python programming

  skills for data pipelines, API integration, and scripting.
• Advanced SQL proficiency with experience in writing and optimizing complex queries.
  
• Experience with version control systems like

  Git

  .
• Strong problem-solving skills, attention to detail, and ability to work in cross-functional teams.
  

Preferred Qualifications

• Exposure to

  cloud platforms

  (AWS, Azure, or GCP).
• Familiarity with

  data lake architecture and real-time streaming technologies

  .
• Knowledge of

  CI/CD pipelines

  for data deployment.
• Experience working in

  agile development methodologies

  .