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 data processing solutions using Python, Pandas, and NumPy
• Design and optimize complex SQL queries and data models in Google 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 accuracy
• Support inventory optimization and master data management initiatives
• Monitor and troubleshoot data pipelines to ensure reliability and performance
• Collaborate with Product, Analytics, and Engineering teams

Requirements

• 5–6 years of experience in Data Engineering or related roles
• Strong hands-on experience with Python, Pandas, and NumPy
• Expertise in Google BigQuery and SQL
• Proven experience with Apache Airflow
• Experience in designing and implementing scalable ETL/ELT pipelines
• Strong skills in API development and integration
• Proficiency with Git version control

Preferred Qualifications

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

About the Company

Müller's Solutions provides advanced technical solutions and expertise to drive business efficiency and data-driven decision-making.