Data Architect - GCP

Role & responsibilities

We are seeking a GCP Data Architect with experience in data modeling and building data pipelines. The ideal candidate should have hands-on experience with GCP services such as Composer, GCS, GBQ, Dataflow, Dataproc, and Pub/Sub. Additionally, the candidate should have a proven track record in designing data solutions, covering everything from data integration to end-to-end storage in bigquery.

• Collaborate with Client's Data Architect: Work closely with client data architects and technical teams to design and develop customized data solutions that meet business requirements.
• Design Data Flows: Architect and implement data flows that ensure seamless data movement from source systems to target systems, facilitating real-time or batch data ingestion, processing, and transformation.
• Data Integration & ETL Processes: Design and manage ETL processes, ensuring the efficient integration of diverse data sources and high-quality data pipelines.
• Build Data Products in GBQ: Work on building data products using Google BigQuery (GBQ), designing data models and ensuring data is structured and optimized for analysis.
• Stakeholder Interaction: Regularly engage with business stakeholders to gather data requirements and translate them into technical specifications, building solutions that align with business needs.
• Ensure Data Quality & Security: Implement best practices in data governance, security, and compliance for both storage and processing of sensitive data.
• Continuous Improvement: Evaluate and recommend new technologies and tools to improve data architecture, performance, and scalability.

Preferred candidate profile

Skills and Experience Required:

• 7 to 10 years of experience in Data Architecture, with a strong focus on cloud platforms like GCP.
• Expertise in Google Cloud Platform (GCP) services including Composer, GCS, GBQ, Dataflow, Dataproc, and Pub/Sub.
• In-depth experience in data modeling, designing schemas, and ensuring efficient data structures in GBQ.
• Strong experience with ETL processes and data integration.
• Knowledge of data governance tools such as Collibra and experience with managing metadata and data lineage.
• Experience with building and optimizing data pipelines in cloud environments.
• Proficiency in designing and implementing data products that support business intelligence, reporting, and analytics.
• Ability to work closely with both business and technical teams, understanding requirements and translating them into effective solutions.
• Strong problem-solving skills, analytical thinking, and attention to detail.

Perks and benefits