8-10 years of experience in data engineering or relevant field.
Proficient in SQL and Python with a focus on medallion/lakehouse architectures.
Experience with Databricks, Snowflake, AWS, or Azure.
Knowledge of industrial protocols: OPC-UA, MQTT, Modbus.
Familiarity with OEE, Six Sigma, SPC, and lean methodologies.
Responsibilities
Build scalable cloud data pipelines for high-volume manufacturing data.
Bridge OT/IT systems for real-time data extraction.
Implement and optimize data architectures using Spark and Kafka.
Apply lean methodologies to drive improvements in manufacturing processes.
Collaborate with cross-functional teams to ensure data integrity and availability.
Benefits
Fully remote work environment.
Opportunities for professional development and training.
Collaborative and innovative work culture.
Flexible work hours to promote work-life balance.
Full Job Description
Role: Data Engineer Location: Remote, USA Duration: Fulltime Employee
Job Overview:
Manufacturing 8-10 years in manufacturing (optional) with hands-on experience in shop floor operations, production planning, and systems including MES, SCADA, and ERP.
Proficient in industrial protocols (OPC-UA, MQTT, Modbus) with ability to bridge OT/IT systems for real-time data extraction.
Applied experience with OEE, Six Sigma, SPC, and lean methodologies to drive measurable gains in yield, uptime, and efficiency.
Data Engineering Skilled in building scalable cloud data pipelines for high-volume manufacturing and IoT data using Spark, Kafka, Airflow, and Delta Lake. Strong SQL and Python proficiency with hands-on experience in medallion/ lakehouse architectures on Databricks, Snowflake, AWS, or Azure.
Qualifications
Must have skills:
Minimum 8 - 10 years of experience.
Strong in SQL and Python proficiency with hands-on experience in medallion/lakehouse architectures on Databricks, Snowflake, AWS, or Azure.
