Data Architect (Manufacturing)

Ascentt is building cutting-edge data analytics & AI/ML solutions for global automotive and manufacturing leaders. We turn enterprise data into real-time decisions using advanced machine learning and GenAI. Our team solves hard engineering problems at scale, with real-world industry impact. Were hiring passionate builders to shape the future of industrial intelligence. We are looking for an experienced

SCADA & Data Architect

to design and implement

industrial data architectures

that integrate

SCADA (Ignition), IoT, Unified Namespace (UNS), and cloud data platforms

. The ideal candidate will have hands-on experience with

Ignition SCADA, HiveMQ (UNS), Azure Data Factory, and Snowflake

, ensuring seamless data flow, scalability, and real-time analytics across industrial systems. Key Responsibilities: Design, develop, and optimize

SCADA (Ignition) and IoT

data architectures for industrial automation. Implement

Unified Namespace (UNS)

using

HiveMQ

to enable real-time data streaming and interoperability. Integrate SCADA and IoT data pipelines with

Azure Data Factory and Snowflake

for efficient storage, processing, and analytics. Develop robust

data ingestion, transformation, and processing

workflows for industrial systems. Ensure high availability, security, and scalability of industrial data platforms. Work with

MQTT, OPC UA, and other industrial communication protocols

for seamless data exchange. Collaborate with cross-functional teams to

optimize industrial data workflows and analytics

. Provide technical leadership and best practices for

SCADA, IoT, and cloud data integration

. Essential Skills & Qualifications: Strong experience with

Ignition SCADA

for industrial automation and control systems. Hands-on expertise with

HiveMQ and Unified Namespace (UNS)

for IoT and data streaming. Experience in designing and implementing

Azure Data Factory

workflows. Proficiency in

Snowflake

for industrial data storage, ETL, and analytics. Knowledge of

MQTT, OPC UA, and industrial IoT protocols

. Experience with

real-time data processing and event-driven architectures

. Strong understanding of

industrial data modeling, pipelines, and cloud integration

. Proficiency in

Python, SQL, or scripting languages

for data processing. Preferred Qualifications: Experience with

edge computing and IoT gateways

. Knowledge of

cybersecurity best practices

for industrial data architectures. Familiarity with

DevOps/MLOps practices

for data pipeline automation.

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