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Cloud Data Architect
2 months ago
Mindsprint is seeking a highly skilled Cloud Data Architect to join our team. As a Cloud Data Architect, you will be responsible for designing, architecting, and implementing scalable data solutions on Google Cloud Platform (GCP) to meet the strategic data needs of our organization.
Key Responsibilities- Design and Implement Data Solutions: Develop and implement scalable data solutions on GCP to meet the strategic data needs of the organization.
- Lead Data Integration: Lead the integration of diverse data sources into a unified data platform, ensuring seamless data flow and accessibility across the organization.
- Develop Data Governance Frameworks: Develop and enforce robust data governance, security, and compliance frameworks tailored to GCP's architecture.
- Collaborate with Cross-Functional Teams: Collaborate with cross-functional teams, including data engineers, data scientists, and business stakeholders, to translate business requirements into technical data solutions.
- Optimize Data Solutions: Optimize data storage, processing, and analytics solutions using GCP services such as BigQuery, Dataflow, and Cloud Storage.
- Drive Best Practices: 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: Conduct regular reviews and audits of the data architecture to ensure alignment with evolving business goals and technology advancements.
- Stay Up-to-Date with Emerging Technologies: Stay informed about emerging GCP technologies and industry trends to continuously improve data solutions and drive innovation.
- 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.