Enterprise Data Platform Architect (GCP | Data Lake | Databricks Job at Tredence Inc., Seattle, WA

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  • Tredence Inc.
  • Seattle, WA

Job Description

About the Role:

We are seeking a highly skilled and experienced Enterprise Data Platform Architect to lead the architecture, design, and implementation of a robust data ecosystem enabling business stakeholders to make data-driven decisions. The role focuses on building and evolving an enterprise-grade data platform on Google Cloud Platform (GCP) , incorporating real-time and batch data ingestion , data governance , and advanced analytics enablement through AI/ML and BI tools.

Key Responsibilities:

  • Lead the architecture, design, and engineering of the Enterprise Data Lake on GCP.
  • Define and implement technical and functional frameworks , data platform roadmap, and future-state architecture.
  • Build and manage data ingestion pipelines from sources including SAP/HANA using in-house and cloud-native frameworks.
  • Implement and maintain real-time and batch data processing using tools like Apache Spark , Kafka , Google Pub/Sub , and Talend .
  • Drive the setup and automation of Databricks Platform to enable scalable data science and machine learning use cases.
  • Ensure data quality and governance using Collibra framework and enforce enterprise standards across the platform.
  • Collaborate with business and technology stakeholders to align data strategy with business goals.
  • Evaluate and onboard emerging technologies and vendors through structured PoCs and technical assessments.
  • Oversee automated infrastructure provisioning and platform scalability using Terraform and other DevOps tools.
  • Enable actionable insights for business teams through Power BI integration and support for enterprise reporting.

Required Skills & Qualifications:

  • 10+ years of experience in data engineering, data architecture , or related roles.
  • Strong hands-on experience with Google Cloud Platform (GCP) services and architecture.
  • Expertise in big data ecosystems including Hadoop, Apache Spark/Spark Streaming, and Kafka.
  • Solid understanding of data ingestion patterns , data lake architecture, and data modeling techniques.
  • Experience with Databricks platform and enabling ML/AI workloads.
  • Proficient in Java and Python for building data pipelines and services.
  • Familiarity with ETL tools such as Talend , and infrastructure-as-code with Terraform .
  • Working knowledge of data governance tools (e.g., Collibra ) and best practices.
  • Experience in integrating with BI tools like Power BI for analytics delivery.
  • Excellent communication and leadership skills with the ability to influence and drive decisions.

Preferred Qualifications:

  • GCP or Databricks certifications.
  • Experience working in hybrid cloud environments or on large enterprise data transformation initiatives.
  • Familiarity with SAP data structures and integration techniques.

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