SeniorStaffEngineer-SeniorDataEngineer

## Accountabilities Design, build, and optimize scalable data pipelines to process high-volume manufacturing and IoT data using modern distributed systems and cloud platforms. Develop and maintain integrations between OT systems (MES, SCADA, PLCs) and IT environments to enable real-time and batch data ingestion. Architect and implement lakehouse and medallion data structures across platforms such as Databricks, Snowflake, AWS, or Azure. Work with industrial protocols (OPC-UA, MQTT, Modbus) to extract, normalize, and stream production data from shop floor systems. Apply manufacturing and process improvement methodologies (OEE, Six Sigma, SPC, Lean) to support performance optimization and operational insights. Build reliable data workflows using tools such as Spark, Kafka, Airflow, and related data engineering technologies. Collaborate with cross-functional teams to translate business and manufacturing requirements into scalable technical solutions. Requirements: 8–10+ years of experience in data engineering, with strong exposure to large-scale data systems and cloud-based architectures. Strong proficiency in SQL and Python for data processing, transformation, and pipeline development. Hands-on experience with modern data platforms such as Databricks, Snowflake, AWS, or Azure. Solid understanding of lakehouse and medallion architecture patterns. Experience working with streaming and batch data processing frameworks such as Spark, Kafka, and Airflow. Familiarity with manufacturing environments, including MES, SCADA, ERP systems, and shop floor operations (preferred). Knowledge of industrial protocols such as OPC-UA, MQTT, and Modbus (strong advantage). Understanding of manufacturing performance metrics and methodologies such as OEE, Six Sigma, and SPC. Strong problem-solving skills with the ability to operate in complex, data-rich environments. Benefits: Competitive compensation package aligned with senior-level engineering expertise. Fully remote work opportunity with