Senior Data Architect at Zeal Group

Shanghai, Shanghai, China -

Full Time

Start Date

Immediate

Expiry Date

17 Jun, 26

Salary

0.0

Posted On

19 Mar, 26

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Data Architect, GCP, BigQuery, dbt, Data Modeling, Airflow, Dagster, ELT Pipelines, SQL, Data Governance, Performance Optimization, Data Quality, Cloud Data Warehouse, Architecture Leadership, Cost Governance, Data Lineage

Industry

Financial Services

Description

Role Overview We are seeking a highly experienced Senior Data Architect to lead the design, evolution, and governance of a cloud-native data warehouse on Google Cloud Platform (GCP). This role owns the overall data architecture vision and ensures the data platform is scalable, secure, cost-efficient, and analytics-ready. You will provide architectural leadership across data engineering and analytics teams, define standards and best practices, and partner with senior stakeholders to enable high-impact data use cases. Key Responsibilities Own and evolve the end-to-end cloud data architecture on GCP, with BigQuery as the core analytical platform Define and enforce enterprise data modeling standards using dbt (dimensional, semantic, and analytics-layer models) Architect and govern ELT pipelines orchestrated by Airflow and/or Dagster, ensuring reliability and scalability Provide technical leadership and architectural guidance to data engineers and analytics engineers Review and approve data designs, dbt models, and pipeline implementations for architectural consistency Drive BigQuery performance optimization and cost governance, including partitioning, clustering, and workload management Establish and mature data quality, testing, observability, and lineage frameworks Define and enforce security, access control, and data governance standards across the data platform Partner with product, analytics, and business leaders to translate complex requirements into scalable data solutions Lead architectural decision-making for new data sources, tools, and platform enhancements Balance business requirements and data platform cost expense, optimize the costs based on target 5+ years of experience in data architecture, data engineering, or analytics engineering roles Proven experience leading the design and implementation of cloud data warehouses Deep hands-on experience with GCP, especially BigQuery Strong expertise in dbt for data modeling, testing, documentation, and deployments Extensive experience with Airflow and/or Dagster for workflow orchestration Advanced SQL skills and strong command of data modeling patterns Experience designing scalable, reliable ELT architectures in production environments Ability to lead architecture discussions and influence technical direction across teams Experience with large-scale or multi-domain data platforms Knowledge of additional GCP services such as Cloud Storage, Dataproc, and IAM Experience enabling BI and semantic layers (e.g. PowerBI, dbt metrics, Cube) Familiarity with data governance, metadata management, and data catalog tools Experience in regulated industries or environments with strict data controls Experience balancing platform scalability with cost efficiency

Responsibilities

This role is responsible for leading the design, evolution, and governance of a cloud-native data warehouse on Google Cloud Platform (GCP), focusing on BigQuery as the core analytical platform. Key duties include defining data modeling standards using dbt and architecting reliable ELT pipelines orchestrated by Airflow and/or Dagster.