Data Engineer

Responsibilities

• Design, develop, and maintain scalable ETL/ELT pipelines for data ingestion and processing
• Build and optimize data workflows using Apache Airflow
• Develop and maintain data processing solutions using Python, Pandas, and NumPy
• Design and optimize complex SQL queries and data models in BigQuery
• Develop and integrate APIs to support data exchange between systems
• Implement data ingestion frameworks from various internal and external sources
• Perform data cleansing, transformation, and validation to ensure data accuracy
• Develop and maintain processes for master data management
• Support inventory optimization initiatives by implementing data processing and business logic
• Build and maintain backend services that enable data-driven applications
• Monitor and troubleshoot data pipelines to ensure reliability and performance
• Collaborate with cross-functional teams including Product, Analytics, and Engineering

Requirements

• 5–6 years of experience in Data Engineering or related roles
• Strong hands-on experience with Python, Pandas, NumPy, Apache Airflow, Google BigQuery, and SQL
• Experience in designing and implementing scalable ETL/ELT pipelines
• Strong understanding of data modeling, data transformation, and database concepts
• Experience working with large-scale datasets and optimizing query performance
• Proficiency with Git

Preferred Qualifications

• Bachelor's degree in Computer Science, Information Technology, Data Science, or a related field
• Experience with PySpark and distributed data processing
• Basic understanding of Machine Learning concepts and workflows
• Familiarity with data quality frameworks and data validation practices
• Experience with Docker and containerization technologies
• Knowledge of CI/CD pipelines and DevOps practices
• Experience working in cloud-based data environments