GCP Data Architect

Key Responsibilities

Design and Implement Data Architectures : Architect and build scalable, end-to-end data solutions on GCP, encompassing data ingestion, transformation, storage, and consumption.

Develop Data Pipelines : Design and develop ETL / ELT data pipelines using tools like Apache Airflow (Cloud Composer) and programming languages such as Python and SQL for batch and real-time processing.

Create Data Models : Build logical and physical data models, including dimensional modelling and schema design, to support data warehousing, data lakes, and analytics.

Ensure Data Quality and Governance : Establish and enforce data governance, security, and quality standards, implementing data validation and testing procedures.

Collaborate with Stakeholders : Work with data engineers, business analysts, data scientists, and product owners to translate business requirements into technical data solutions.

Optimize GCP Services : Optimize the performance and cost-effectiveness of GCP services, particularly Big Query, for analytics and data storage.

Provide Technical Guidance : Lead architectural reviews, provide technical guidance on cloud-native data strategies, and mentor engineering teams on GCP best practices.

Required Skills and Knowledge

Google Cloud Platform (GCP) : Expertise with GCP services like BigQuery, Cloud Storage, Cloud SQL, and Cloud Composer.

Data Modelling : Proficiency in designing data models for data warehouses and data lakes.

ETL / ELT : Experience with designing and building data pipelines using tools like Apache Airflow.

Programming : Strong skills in SQL and Python for data processing and development.

Data Governance : Understanding and ability to implement data governance, metadata management, and security policies.

Collaboration : Strong communication skills to work with cross-functional teams and explain complex technical concepts.