Data Engineer

Key Responsibilities

• Design, develop, and optimize data pipelines and ETL processes using modern data engineering tools and technologies
• Apply domain expertise in operations, supply chain, and manufacturing to deliver tailored data solutions
• Process and analyze large-scale operational datasets using frameworks like Apache Spark
• Implement data transformations and business logic to support analytics and decision-making
• Manage structured and semi-structured data on cloud platforms such as Snowflake
• Use dbt for data modeling, transformation, and documentation to ensure consistency and quality
• Monitor, troubleshoot, and enhance the performance and scalability of data pipelines
• Conduct data profiling, cleansing, and validation to ensure high data integrity
• Collaborate with cross-functional teams including operations, data science, and business analysts to deliver impactful solutions
• Stay updated with the latest trends and emerging tools in the data engineering ecosystem

Preferred Qualifications

• Bachelor's degree in Computer Science, Engineering, Operations Management, or a related field
• Minimum of 5 years of experience in data engineering or related roles
• Proficiency in Python, Spark, SQL, Snowflake, dbt, and associated tools
• Strong understanding of data within operations, supply chain, or manufacturing domains
• Experience with big data frameworks and working on cloud platforms (e.g., AWS, Azure, GCP)
• Solid knowledge of data modeling, ETL development, and data integration best practices
• Familiarity with visualization tools like Tableau or Power BI is a plus
• Strong analytical, problem-solving, and communication skills