Architect Senior Associate

Summary
Seeking a highly hands-on Data Architect with a strong data engineering background to design, build, and optimize scalable analytics and data platforms on Google Cloud Platform. This role emphasizes hands-on development over pure architecture, requiring deep experience with data pipelines, BigQuery, SQL, and modern transformation frameworks such as dbt or Dataform. The ideal candidate can translate complex business requirements into well-governed data architectures while remaining actively involved in coding, pipeline development, performance optimization, and deployment. This is a HYBRID role supporting large-scale enterprise analytics and operational use cases.

Key Responsibilities

• Design, build, and maintain scalable data pipelines on Google Cloud Platform (GCP), using Dataflow for batch and streaming workloads.
• Develop and manage data transformation layers using Dataform and/or dbt, following best practices for modeling, testing, documentation, and deployment.
• Design end-to-end enterprise data architectures to support large-scale analytics and operational use cases.
• Translate complex business requirements into conceptual, logical, and physical data models.
• Apply advanced BigQuery expertise, including schema design, partitioning, clustering, and cost/performance optimization.
• Write complex, high-performance SQL for large-scale data transformations and analytics.
• Leverage programming skills (Python, Java, Scala, or similar) to support automation, pipeline logic, orchestration, and utilities.
• Develop and maintain standards-compliant data models using enterprise modeling tools (e.g., SAP PowerDesigner, ERwin).
• Collaborate within CI/CD and Git-based workflows, including code reviews, testing, and managed deployments.
• Bridge hands-on data engineering execution with data architecture best practices and governance.

Qualifications

• Bachelor’s degree in a related field.
• Strong hands-on background in data engineering and software development.
• Experience designing and building data pipelines and analytics platforms on GCP.
• Proficiency with BigQuery, SQL, and data modeling techniques.
• Strong programming skills in Python, Java, Scala, or equivalent.
• Practical experience with data architecture concepts for analytics systems.
• Ability to design, build, and optimize production-grade data systems end to end.

Experience

• Senior-level experience (typically 6–10 years in IT, with 4+ years in data engineering, analytics, or related specialization).
• Experience is evaluated based on demonstrated technical capability rather than years alone.