Data Architect

Design source-to-target mappings and logical/physical data models for enterprise warehouse or integration platforms
Architect and support data solutions using Google BigQuery and GCP data services
Orchestrate batch ETL pipelines with Apache Airflow or Cloud Composer
Develop and optimize complex SQL for analytics and ETL
Review and critique ETL code and SQL
Mentor developers on implementation quality
Debug end-to-end data pipelines from source through reporting
Apply enterprise dimensional modeling practices
Produce client-facing specifications and developer-facing implementation guides
Collaborate across time zones with offshore development teams using structured ticketing systems

Requirements

• 8+ years in data engineering, analytics engineering, or data architecture
• 4+ years in an architect or senior Business-As-Us-ual (BAU) production-support capacity
• Demonstrated experience creating source-to-target mappings and logical/physical data models for enterprise warehouse or integration platforms
• Deep hands-on experience with Google BigQuery and GCP data services, including Cloud Storage, IAM, and multi-project patterns
• Strong experience with Apache Airflow or Cloud Composer for batch ETL orchestration
• Expert-level SQL for complex analytics and ETL, including CTEs, window functions, incremental logic, deduplication, and SCD2
• Proven ability to review and critique ETL code/SQL and mentor developers on implementation quality
• Proven ability to debug end-to-end data pipelines: source → lake → integration dims/facts → reporting
• Experience with enterprise dimensional modeling, including star/snowflake schemas, conformed dimensions, fact grain, and bridge tables
• Excellent written communication; able to produce client-facing specifications and developer-facing implementation guides from the same design
• Comfortable working across time zones with offshore development teams and structured ticketing such as Jira or equivalent

Core Competencies

Demonstrates extensive experience in data engineering and architecture, with a strong focus on designing data models and orchestrating ETL pipelines using Google BigQuery and Apache Airflow. Proven ability to mentor developers and produce comprehensive documentation for both clients and technical teams.

Highest-signal resume keywords

• Data Engineering
• Google BigQuery
• Apache Airflow
• SQL Expertise
• Enterprise Dimensional Modeling

Hard Skills

• Data Modeling
• ETL Development
• SQL Optimization
• Debugging Data Pipelines
• Source-to-Target Mapping
• Dimensional Modeling
• Incremental Logic
• SCD2
• Cloud Storage
• IAM

Soft Skills

• Written Communication
• Mentoring

Industry Keywords

• Data Architecture
• Analytics Engineering
• Batch ETL
• Integration Platforms
• Star Schema
• Snowflake Schema

Tools & Technologies

• GCP Data Services
• Cloud Composer
• Jira