Data Architect

- 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, ensuring seamless data flow and accessibility across the organization. - Develop and enforce robust data governance, security, and compliance frameworks tailored to GCP's architecture. Collaborate with cross-functional teams, including data engineers, data scientists, and business stakeholders, to translate business requirements into technical data solutions. - Optimize data storage, processing, and analytics solutions using GCP services such as Big Query, Dataflow, and Cloud Storage. - Drive the adoption of best practices in data architecture and cloud computing to enhance the performance, reliability, and scalability of data solutions. - Conduct regular reviews and audits of the data architecture to ensure alignment with evolving business goals and technology advancements. - Stay informed about emerging GCP technologies and industry trends to continuously improve data solutions and drive innovation. Profile Description: - Experience: 12-15 years of experience in data architecture, with extensive expertise in Google 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 data warehousing. - Qualifications: Masters degree in Computer Science, Data Engineering, or a related field. - Competencies: Strong leadership abilities, with a proven track record of managing large-scale data projects. - Ability to balance technical and business needs in designing data solutions. Certifications: Google Cloud Professional Data Engineer or Professional Cloud Architect certification preferred. - Knowledge: Extensive knowledge of data governance, security best practices, and compliance in cloud environments. - Familiarity with big data technologies like Apache Hadoop and Spark. - Soft Skills: Excellent communication skills to work effectively with both technical teams and business stakeholders. - Ability to lead and mentor a team of data engineers and architects. 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. Required abilities Physical: Other: - Work Environment Details: Specific requirements Travel: - Vehicle: - Work Permit: - Other detailsPay Rate: Contract Types: - Time Constraints: - Compliance Related: - Union Affiliation: Skills: Git, Power Bi, Sql, Python Experience: 12.00-15.00 Years