Data Architect, DC Digital Infrastructure

Dallas - USA

Monthly Salary: Not Disclosed

Posted on: 30+ days ago

Vacancies: 1 Vacancy

Job Summary

We are seeking an experienced Data Architect to own the data strategy architecture and governance of the data platform underpinning our next-generation data center. This role is key in structuring securing and optimizing the data flows from OT/IT systems sensors and business platforms into a unified analytics and AI-ready data environment. This role will work closely with the Digital Architect with a focus in systems integration to deliver a seamless digital and data ecosystem.

Responsibilities:

Own the end-to-end data architecture for operational and business datasets including OT telemetry IoT sensor data asset performance metrics and other KPIs.
Design and maintain the enterprise data model ensuring consistency across disparate systems (BMS EPMS CMMS ERP etc).
Define and oversee data ingestion and transformation pipelines for both real-time and batch processing.
Architect and manage cloud-based data infrastructure (e.g. AWS Glue GCP Dataflow Azure Synapse) to ensure scalability and reliability.
Select implement and optimise time-series relational and analytical data platforms (e.g. InfluxDB Snowflake BigQuery).
Establish data lake and/or lakehouse architecture for scalable flexible storage and analytics.
Define and enforce data governance policies including access control data retention and regulatory compliance.
Implement and maintain data quality lineage and metadata management frameworks.
Deploy and manage data cataloging tools to support data discoverability self-service analytics and compliance.
Evaluate and pilot emerging tools and platforms to continuously improve data infrastructure and support innovation initiatives.
Define API and integration standards for all consuming/producing systems.
Collaborate with security teams to design secure data architectures and implement role-based access controls (RBAC).
Define and manage versioning and lifecycle policies for data models schemas and APIs across environments.
Collaborate cross-functionally to deliver high-quality trusted datasets to power predictive analytics simulation digital twin initiatives and business reporting.

Requirements:

Bachelor s or Master s in Computer Science Data Engineering or related field.
7 years of data architecture or data engineering experience in mission-critical or industrial environments (data centers manufacturing smart buildings energy systems).
Experience in data modeling and data governance frameworks.
Experience designing and implementing time-series data platforms and streaming architectures.
Expertise in ETL/ELT tools and modern data stack tools (e.g. dbt Kafka Spark Airflow) and platforms such as Snowflake BigQuery Databricks etc
Familiarity with OT/IoT protocols (BACnet Modbus OPC-UA) and integrating operational data into IT systems.
Strong knowledge of cloud-native analytics platforms (AWS GCP Azure) and edge data processing strategies.
Excellent cross-functional communication skills able to bridge engineering operations and analytics teams.

Responsibilities:

Own the end-to-end data architecture for operational and business datasets including OT telemetry IoT sensor data asset performance metrics and other KPIs.
Design and maintain the enterprise data model ensuring consistency across disparate systems (BMS EPMS CMMS ERP etc).
Define and oversee data ingestion and transformation pipelines for both real-time and batch processing.
Architect and manage cloud-based data infrastructure (e.g. AWS Glue GCP Dataflow Azure Synapse) to ensure scalability and reliability.
Select implement and optimise time-series relational and analytical data platforms (e.g. InfluxDB Snowflake BigQuery).
Establish data lake and/or lakehouse architecture for scalable flexible storage and analytics.
Define and enforce data governance policies including access control data retention and regulatory compliance.
Implement and maintain data quality lineage and metadata management frameworks.
Deploy and manage data cataloging tools to support data discoverability self-service analytics and compliance.
Evaluate and pilot emerging tools and platforms to continuously improve data infrastructure and support innovation initiatives.
Define API and integration standards for all consuming/producing systems.
Collaborate with security teams to design secure data architectures and implement role-based access controls (RBAC).
Define and manage versioning and lifecycle policies for data models schemas and APIs across environments.
Collaborate cross-functionally to deliver high-quality trusted datasets to power predictive analytics simulation digital twin initiatives and business reporting.

Requirements:

Bachelor s or Master s in Computer Science Data Engineering or related field.
7 years of data architecture or data engineering experience in mission-critical or industrial environments (data centers manufacturing smart buildings energy systems).
Experience in data modeling and data governance frameworks.
Experience designing and implementing time-series data platforms and streaming architectures.
Expertise in ETL/ELT tools and modern data stack tools (e.g. dbt Kafka Spark Airflow) and platforms such as Snowflake BigQuery Databricks etc
Familiarity with OT/IoT protocols (BACnet Modbus OPC-UA) and integrating operational data into IT systems.
Strong knowledge of cloud-native analytics platforms (AWS GCP Azure) and edge data processing strategies.
Excellent cross-functional communication skills able to bridge engineering operations and analytics teams.