Data Engineer

Streamline Innovations•San Antonio, TX

About The Position

We are seeking a Data Engineer passionate about bridging operational technology (OT) and information technology (IT). In this role, you will design and implement scalable data platforms that transform industrial and process control data into actionable intelligence. You will work at the intersection of data engineering, cloud, and industrial automation, helping build out our Industry 4.0 infrastructure by connecting plant-floor systems (PLCs, SCADA, historians, sensors) to advanced analytics, dashboards, and AI-driven decision-support tools.

Requirements

Bachelor’s or Master’s degree in Computer Science, Data Engineering, or a related engineering discipline
4+ years of experience in software or data engineering, with solid experience in industrial or IIoT data integration
Expertise in Python, SQL, and API development (REST/GraphQL)
Familiarity with industrial data protocols (MQTT, OPC UA, Modbus, BACnet) and SCADA/MES connectivity
Experience with cloud platforms (AWS, Azure, or GCP) for ingestion, storage, and analytics
Strong understanding of front-end frameworks (React, Angular, or Vue)
Experience with data orchestration tools and container technologies (Airflow, Docker, Kubernetes)
Proven ability to design reliable, maintainable, and secure data architectures for OT/IT convergence

Nice To Haves

Certification through IIoT University’s Mentorship or Mastermind Program
Hands-on experience with Ignition (Inductive Automation), Aveva, or Rockwell Automation ecosystems
Familiarity with process historians (OSIsoft PI, Canary, Aspen IP.21)
Background in manufacturing, chemical, or energy operations environments
Exposure to edge computing architectures or data streaming from embedded or plant-floor devices

Responsibilities

Architect, develop, and maintain data pipelines that integrate IIoT, SCADA, and MES sources into cloud-based data platforms
Build APIs and microservices to serve real-time and historical process data to analytics and visualization applications
Develop user-facing applications and dashboards (React, Vue, or similar) for operations, reliability, and performance optimization
Implement and maintain data models and transformation workflows using modern tools like dbt, Airflow, or Prefect
Design efficient data storage schemas in time-series and analytical databases (e.g., InfluxDB, TimescaleDB, Snowflake)
Deploy and manage streaming and messaging infrastructure (MQTT, Kafka, OPC UA servers, or Ignition gateways)
Collaborate with data scientists, control engineers, and IT/OT teams to support predictive maintenance, process analytics, and digital twin initiatives
Apply DevOps best practices, including CI/CD for data pipelines, containerization, and infrastructure automation