> Markdown version of [/jobs/ext/1976807-manufacturing-data-engineer](https://www.wearedevelopers.com/jobs/ext/1976807-manufacturing-data-engineer). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Manufacturing Data Engineer - **Company:** Randstad - **Location:** Plano, TX, United States - **Experience:** Experienced - **Salary:** $140,000.0 - $145,000.0 - **Contract:** Permanent contract - **Skills:** A/B Testing, Airflow, Amazon Web Services, Microsoft Azure, Communications Protocols, Data Architecture, Information Engineering, Supervisory Control and Data Acquisition (SCADA), Statistical Hypothesis Testing, Python (Programming Language), Modbus, Message Queuing Telemetry Transport (MQTT), Tensorflow, Standard Sql, OPC Unified Architecture, Statistical Process Control (SPC), Technical Data Management Systems, Pytorch, Snowflake, Apache Spark, Data Strategy, Data Lakes, Scikit Learn, Information Technology, Data Analytics, Real Time Data, Apache Kafka, Machine Learning Operations, Data Pipelines, Databricks - **Published:** August 7, 2026 - **Apply:** https://www.dice.com/job-detail/424d9314-beb8-49e8-bc01-fbd0fac377b6 ## About the Role Must-Haves: Proven expertise in data engineering, specifically building and scaling cloud pipelines using modern frameworks. Hands-on experience working with tools such as Spark, Kafka, Airflow, and Delta Lake for high-volume data architecture. Exceptional communication and storytelling skills, with the ability to bridge the gap between deep technical data outputs and high-level business strategy. Demonstrated experience designing A/B tests, hypothesis testing, and operational simulations. Nice-to-Haves: Two to four years of professional background working directly within the manufacturing, supply chain, or industrial domains. Familiarity with shop floor operations and systems such as MES, SCADA, and ERP platforms. Working knowledge of industrial communication protocols (OPC-UA, MQTT, Modbus) to bridge OT and IT systems. Practical application of lean methodologies, Six Sigma, SPC, and OEE to drive measurable gains in yield and uptime. Experience moving predictive models from prototype to production using scikit-learn, TensorFlow, or PyTorch. A strong foundation in advanced statistical methods, including time series analysis, regression, and clustering for manufacturing quality control. Skills Cloud Data Pipelines Apache Spark & Kafka Airflow & Delta Lake IoT Data Processing A/B Testing & Simulation Executive Communication OT/IT System Integration Industrial Protocols (OPC-UA, MQTT, Modbus), Proven expertise in data engineering, specifically building and scaling cloud pipelines using modern frameworks. Hands-on experience working with tools such as Spark, Kafka, Airflow, and Delta Lake for high-volume data architecture. Exceptional communication and storytelling skills, with the ability to bridge the gap between deep technical data outputs and high-level business strategy. Demonstrated experience designing A/B tests, hypothesis testing, and operational simulations. Nice-to-Haves: Two to four years of professional background working directly within the manufacturing, supply chain, or industrial domains. Familiarity with shop floor operations and systems such as MES, SCADA, and ERP platforms. Working knowledge of industrial communication protocols (OPC-UA, MQTT, Modbus) to bridge OT and IT systems. Practical application of lean methodologies, Six Sigma, SPC, and OEE to drive measurable gains in yield and uptime. Experience moving predictive models from prototype to production using scikit-learn, TensorFlow, or PyTorch. A strong foundation in advanced statistical methods, including time series analysis, regression, and clustering for manufacturing quality control. skills: Airflow,AWS,Kafka,Spark,Delta Lake,Databricks,Data Engineering,IT systems,deploying ML models,MQTT,Azure,Modbus,OPC-UA,Python proficiency,PyTorch,real-time data,Snowflake,Strong SQL,hypothesis testing,SPC,SCADA,TensorFlow,communicator,business impact,anomaly detection,prototype,Data Science,demand forecasting,ERP,experiments,statistical methods,lean methodologies,manufacturing,manufacturing quality,OEE,predictive maintenance,production planning,root cause analysis,simulations,Six Sigma,IoT data,time series ## Description Here is the rewritten, highly optimized job advertisement tailored for RD1 and external job boards, ensuring complete client confidentiality and maximum candidate engagement., As a key driver of our client's data strategy, a typical day in this role will involve: Designing, building, and maintaining robust cloud-based data pipelines to seamlessly process high-volume IoT and continuous manufacturing data streams. Translating intricate machine learning model outputs and complex analytics into clear, strategic recommendations for shop floor operations teams and executive leadership. Developing and executing A/B experiments and digital simulations to validate proposed process modifications before wide-scale production rollout. Partnering with cross-functional technical and business units to quantify the real-world impact of data-driven process improvements., * Data Engineering Skilled in building scalable cloud data pipelines for high-volume manufacturing and IoT data using Spark, Kafka, Airflow, and Delta Lake. * Strong communicator - able to translate complex model outputs into clear, actionable recommendations for operations and executive stakeholders. * Experience designing A/B experiments and simulations to validate process changes and quantify business impact before full deployment. ## Related Videos - [From Messy Queries to Scalable Systems - How Data Engineering actually works](https://www.wearedevelopers.com/videos/100203-from-messy-queries-to-scalable-systems-how-data-engineering-actually-works) - [Industrializing your Data Science capabilities](https://www.wearedevelopers.com/videos/178-industrializing-your-data-science-capabilities) - [Photonic Computing: Programming a New Class of AI Accelerators (incl. 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