Senior Data Architect

Job Description:Design, architect, and implement scalable data solutions on Google Cloud Platform(GCP) to meet the strategic data needs of the organization.Lead the integration of diverse data sources into a unified data platform, ensuringseamless data flow and accessibility across the organization.Develop and enforce robust data governance, security, and compliance frameworkstailored to GCP's architecture.Collaborate with cross-functional teams, including data engineers, data scientists, andbusiness stakeholders, to translate business requirements into technical datasolutions.Optimize data storage, processing, and analytics solutions using GCP services suchas BigQuery, Dataflow, and Cloud Storage.Drive the adoption of best practices in data architecture and cloud computing toenhance the performance, reliability, and scalability of data solutions.Conduct regular reviews and audits of the data architecture to ensure alignment withevolving business goals and technology advancements.Stay informed about emerging GCP technologies and industry trends to continuouslyimprove data solutions and drive innovation.Profile Description:Experience: 12+ years of total IT experience in data architecture, with extensive expertise inGoogle Cloud Platform (GCP).Skills: Deep understanding of GCP services including BigQuery, Dataflow, Pub/Sub,Cloud Storage, and IAM. Proficiency in data modeling, ETL processes, and datawarehousing.Qualifications: Master's degree in Computer Science, Data Engineering, or a relatedfield.Competencies: Strong leadership abilities, with a proven track record of managinglarge-scale data projects. Ability to balance technical and business needs in designingdata solutions.Certifications: Google Cloud Professional Data Engineer or Professional CloudArchitect certification preferred.Knowledge: Extensive knowledge of data governance, security best practices, andcompliance in cloud environments. Familiarity with big data technologies like ApacheHadoop and Spark.Soft Skills: Excellent communication skills to work effectively with both technical teamsand business stakeholders. Ability to lead and mentor a team of data engineers andarchitects.Tools: Experience with version control (Git), CI/CD pipelines, and automation tools.Proficient in SQL, Python, and data visualization tools like Looker or Power BI.