GCP Cloud Data Architect

3 days ago

Canada Intuitive Full time

About us:

Intuitive is an innovation-led engineering company delivering business outcomes for 100's of Enterprises globally. With the reputation of being a Tiger Team & a Trusted Partner of enterprise technology leaders, we help solve the most complex Digital Transformation challenges across following Intuitive Superpowers:

Modernization & Migration

  • Application & Database Modernization
  • Platform Engineering (IaC/EaC, DevSecOps & SRE)
  • Cloud Native Engineering, Migration to Cloud, VMware Exit
  • FinOps

Data & AI/ML

  • Data (Cloud Native / DataBricks / Snowflake)
  • Machine Learning, AI/GenAI

Cybersecurity

  • Infrastructure Security
  • Application Security
  • Data Security
  • AI/Model Security

SDx & Digital Workspace (M365, G-suite)

  • SDDC, SD-WAN, SDN, NetSec, Wireless/Mobility
  • Email, Collaboration, Directory Services, Shared Files Services

Intuitive Services:

  • Professional and Advisory Services
  • Elastic Engineering Services
  • Managed Services
  • Talent Acquisition & Platform Resell Services

About the job:

Title: GCP Cloud Data Architect

Position Type: Contract

Location: Remote across USA/ Canada

Key Responsibilities:

MDE Implementation & Configuration:

  • Design, configure, and deploy Google Cloud's Manufacturing Data Engine solution tailored to our specific midstream operational landscape.
  • Architect and build robust, scalable data pipelines using core MDE components like Pub/Sub, Dataflow, and Data Fusion to ingest real-time and batch data from OT sources (SCADA, DCS, PLCs, Historians like OSIsoft PI, IoT sensors) and IT systems (ERP, MES, LIMS, maintenance logs).
  • Implement data processing logic within Dataflow for cleaning, transforming, and preparing data for analytics.

Data Integration & Contextualization:

  • Focus heavily on data contextualization, integrating time-series operational data with relevant IT data (e.g., asset information, work orders, material specs) within the MDE framework.
  • Develop and implement strategies for mapping disparate data sources into a unified data model within BigQuery, leveraging MDE's capabilities.
  • Work with operations and engineering teams to define the necessary context for meaningful analysis.

Data Modeling & Analytics Enablement:

  • Design and optimize data models in BigQuery specifically for storing and analyzing contextualized manufacturing/operational data, supporting time-series analysis, anomaly detection, and reporting.
  • Manage data storage effectively within Cloud Storage and BigQuery, considering cost, performance, and data lifecycle requirements.
  • Prepare and structure data to enable consumption by downstream analytics tools (Looker, other BI platforms) and AI/ML models (Vertex AI).

Platform Health & Optimization:

  • Monitor the health, performance, and cost-efficiency of the MDE instance and associated data pipelines.
  • Implement robust data quality checks, validation rules, and monitoring specific to operational data integrity within the MDE pipeline.
  • Troubleshoot and resolve issues related to data ingestion, processing, storage, and accessibility within the MDE environment.
  • Utilize Infrastructure as Code (IaC) tools (e.g., Terraform) and CI/CD practices for managing and deploying MDE configurations and data pipelines.

Collaboration & Governance:

  • Collaborate closely with process engineers, control systems specialists, maintenance teams, data scientists, and business analysts to understand requirements and translate them into MDE solutions.
  • Ensure data security, access control (IAM), and compliance with industry regulations and internal policies within the GCP environment.
  • Document the MDE architecture, data flows, contextualization logic, and operational procedures.

Required Qualifications:

  • Bachelor's degree in Computer Science, Engineering, Information Technology, or a related quantitative field.
  • 3-5+ years of hands-on experience as a Data Engineer.
  • Proven experience designing, building, and managing data pipelines on Google Cloud Platform (GCP).
  • Strong proficiency with core GCP data services: BigQuery, Dataflow, Pub/Sub, Cloud Storage.
  • Excellent programming skills in Python and SQL.
  • Experience with ETL/ELT development for both streaming and batch processing.
  • Understanding of data warehousing, data modeling (especially time-series and contextual models), and database concepts.
  • Familiarity with software development best practices (Git, CI/CD, testing).
  • Excellent analytical and problem-solving skills.
  • Strong communication skills, capable of bridging the gap between technical teams and operational stakeholders.

Preferred Qualifications:

  • Direct experience implementing or working extensively with Google Cloud's Manufacturing Data Engine (MDE).
  • Experience integrating data from industrial OT systems (SCADA, DCS, PLCs, OSIsoft PI Historian or similar).
  • Familiarity with industrial communication protocols (e.g., OPC-UA, Modbus).
  • Experience with data contextualization techniques, merging OT and IT data.
  • Experience in the Midstream Oil & Gas sector or related heavy manufacturing/process industries.
  • Experience with GCP Data Fusion, Cloud Composer (Airflow), or Vertex AI.
  • Experience using Looker or other BI tools for visualizing operational data.
  • Knowledge of IT systems like ERP (e.g., SAP, Oracle) or MES.
  • Experience with Infrastructure as Code (Terraform).
  • GCP Professional Data Engineer certification.

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