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