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+ years of total IT 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.
