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, 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 BigQuery, 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: Master’s 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.