Data Engineer

We are looking for skilled Data Engineers with hands-on experience in Snowflake, SQL, PySpark, AWS, and Airflow to design, develop, and support scalable data pipelines and data transformation frameworks. Candidates should have experience in ETL/ELT development, data validation, troubleshooting, and performance optimization. Knowledge of Data Vault 2.0 and DBT/Coalesce is highly desirable.

Key Responsibilities

• Design, develop, and maintain scalable ETL/ELT data pipelines.
• Work with Snowflake, SQL, PySpark, AWS, and Airflow to build and manage data engineering solutions.
• Develop and optimize SQL queries and PySpark jobs for efficient data processing.
• Perform data validation, data reconciliation, and source-to-target verification.
• Troubleshoot pipeline failures, investigate data quality issues, and provide production support.
• Monitor pipeline performance and implement performance-tuning techniques.
• Work on data transformation frameworks using DBT/Coalesce and Data Vault 2.0 methodologies, as applicable.
• Collaborate with cross-functional teams to deliver reliable and high-quality data solutions.

Required Skills

• Strong hands-on proficiency in SQL and PySpark.
• Practical experience with Snowflake, AWS, and Airflow.
• Experience in developing and supporting ETL/ELT pipelines.
• Understanding of data transformation, data validation, and troubleshooting.
• Knowledge of Data Vault 2.0 and DBT/Coalesce.
• Good analytical, problem-solving, and communication skills.

Experience-Based Requirements

Junior Data Engineer 2 to 5 Years

• Hands-on experience with Snowflake, SQL, PySpark, AWS, and Airflow.
• Experience developing and supporting ETL/ELT pipelines.
• Basic understanding of Data Vault 2.0 and DBT/Coalesce.
• Ability to perform basic data validation, troubleshooting, and performance analysis.

Data Engineer 5 to 8 Years

• Medium to strong hands-on experience implementing Data Vault 2.0 and DBT/Coalesce.
• Strong hands-on experience with Snowflake, SQL, PySpark, AWS, and Airflow.
• Ability to own end-to-end ELT pipelines and data transformation frameworks.
• Experience in performance tuning, troubleshooting, and production support.
• Strong experience with data reconciliation and source-to-target validation.

Preferred Qualifications

• Experience working on enterprise-scale data engineering projects.
• Understanding of data modeling, data quality, and pipeline orchestration.
• Ability to work independently and collaborate effectively with technical teams.