Data Engineer

Key Responsibilities

• Design, develop, and maintain scalable data pipelines using PySpark and AWS services
• Build and optimize data models and data warehouses in Snowflake
• Develop efficient SQL queries for data transformation and analysis
• Integrate data from multiple sources (structured and unstructured)
• Ensure data quality, integrity, and governance across systems
• Collaborate with data scientists, analysts, and business stakeholders
• Implement performance tuning and cost optimization strategies
• Monitor and troubleshoot data workflows and pipelines
• Follow best practices for data security and compliance

Required Skills & Qualifications

• 10–12 years of experience in data engineering or related field
• Strong hands-on experience with:
  • AWS (S3, Glue, Lambda, Redshift, EMR, etc.)
  • Snowflake Data Warehouse
  • PySpark / Apache Spark
  • Advanced SQL
• Experience building ETL/ELT pipelines
• Strong understanding of data warehousing concepts and architecture
• Experience with workflow orchestration tools (Airflow preferred)
• Knowledge of data modeling techniques (Star/Snowflake schema)
• Familiarity with version control systems (Git)

Preferred Qualifications

• Experience with real-time data processing (Kafka, Kinesis)
• Knowledge of DevOps practices and CI/CD pipelines
• Exposure to data governance and security frameworks
• AWS or Snowflake certifications are a plus