Data Architect (GCP)

As a Data Architect (GCP) at our company, you will play a crucial role in designing and implementing robust, scalable, and secure data solutions for enterprise environments on Google Cloud Platform (GCP). Your responsibilities will involve architecting data platforms, designing end-to-end data pipelines, and ensuring governance and optimization while aligning with the business strategy. **Key Responsibilities:** - Architect and design data platforms on GCP utilizing services like BigQuery, Dataflow, Pub/Sub, and Cloud Storage. - Develop and maintain conceptual, logical, and physical data models to support BI, analytics, and AI/ML use cases. - Collaborate with cross-functional teams to define data strategy, architecture standards, and governance frameworks. - Lead the migration and modernization of legacy data systems to GCP-based solutions. - Design and implement ETL/ELT pipelines using GCP-native and open-source tools. - Ensure data quality, security, and compliance across platforms. - Optimize performance, cost, and scalability of cloud-based data systems. - Guide and mentor data engineers and analysts on architectural best practices. - Work closely with stakeholders to translate business requirements into scalable data solutions. **Qualifications Required:** - 10-11 years of total experience, with a minimum of 4+ years in data architecture. - Hands-on experience with GCP services like BigQuery, Dataflow, Pub/Sub, Cloud Composer, and Cloud Storage. - Proficiency in data modeling (OLTP, OLAP, dimensional modeling, star/snowflake schemas). - Expertise in SQL, Python, and ETL/ELT design patterns. - Experience in implementing data governance, lineage, and metadata management. - Understanding of data integration, MDM, and security frameworks. In addition to the above, exposure to AI/ML data pipelines, real-time analytics platforms, Terraform or Infrastructure-as-Code (IaC), Snowflake, Apache Beam, or Databricks would be beneficial. Certifications such as Google Professional Data Engineer are preferred. As a professional in this role, you are expected to possess excellent analytical, problem-solving, and architectural thinking skills. Strong communication and stakeholder management abilities are essential. Being self-driven, detail-oriented, and capable of leading data modernization initiatives will be key to your success in this position. As a Data Architect (GCP) at our company, you will play a crucial role in designing and implementing robust, scalable, and secure data solutions for enterprise environments on Google Cloud Platform (GCP). Your responsibilities will involve architecting data platforms, designing end-to-end data pipelines, and ensuring governance and optimization while aligning with the business strategy. **Key Responsibilities:** - Architect and design data platforms on GCP utilizing services like BigQuery, Dataflow, Pub/Sub, and Cloud Storage. - Develop and maintain conceptual, logical, and physical data models to support BI, analytics, and AI/ML use cases. - Collaborate with cross-functional teams to define data strategy, architecture standards, and governance frameworks. - Lead the migration and modernization of legacy data systems to GCP-based solutions. - Design and implement ETL/ELT pipelines using GCP-native and open-source tools. - Ensure data quality, security, and compliance across platforms. - Optimize performance, cost, and scalability of cloud-based data systems. - Guide and mentor data engineers and analysts on architectural best practices. - Work closely with stakeholders to translate business requirements into scalable data solutions. **Qualifications Required:** - 10-11 years of total experience, with a minimum of 4+ years in data architecture. - Hands-on experience with GCP services like BigQuery, Dataflow, Pub/Sub, Cloud Composer, and Cloud Storage. - Proficiency in data modeling (OLTP, OLAP, dimensional modeling, star/snowflake schemas). - Expertise in SQL, Python, and ETL/ELT design patterns. - Experience in implementing data governance, lineage, and metadata management. - Understanding of data integration, MDM, and security frameworks. In addition to the above, exposure to AI/ML data pipelines, real-time analytics platforms, Terraform or Infrastructure-as-Code (IaC), Snowflake, Apache Beam, or Databricks would be beneficial. Certifications such as Google Professional Data Engineer are preferred. As a professional in this role, you are expected to possess excellent analytical, problem-solving, and architectural thinking skills. Strong communication and stakeholder management abilities are essential. Being self-driven, detail-oriented, and capable of leading data modernization initiatives will be key to your success in this position.