Role and Responsibilities :

As an Enterprise Architect, you will :

- Lead the design and development of end-to-end data architectures on the Google Cloud Platform, focusing on scalability, reliability, and cost-effectiveness.

- Architect and build data pipelines and workflows using GCP services such as BigQuery, Cloud Dataflow, Cloud Pub/Sub, Cloud Composer, and Dataform.

- Work closely with stakeholders to understand data requirements and translate them into technical solutions.

- Provide technical leadership and guidance to data engineering teams, ensuring best practices for data governance, security, and quality are followed.

- Define and enforce architectural standards, patterns, and principles for data solutions.

- Oversee the implementation of CI/CD pipelines for data workflows using tools like Jenkins, GitHub, or Bitbucket.

- Utilize Infrastructure as Code (IaC) tools like Terraform or Ansible to manage and automate infrastructure provisioning.

- Stay informed about new GCP services and data technologies, recommending and implementing innovations to enhance our data platform.

Qualifications :

Education : Bachelor's or master's degree in Computer Science, Information Technology, Engineering, or a related field.

Experience :

- Minimum of 10+ years of experience in data engineering, with at least 4 years of hands-on experience on GCP.

- Proven experience in designing and implementing complex data workflows and architectures on a cloud platform.

Certifications :

- Google Cloud Professional Data Engineer certification is strongly preferred.

Required Technical Skills :

- Advanced proficiency in Python for developing data pipelines, automation, and scripting.

- Strong SQL skills for advanced querying, data transformation, and analysis.

- Deep, hands-on experience with core GCP services, including :

- Data Services : BigQuery, Dataform, Cloud Dataflow, Cloud Pub/Sub, Cloud Storage, Cloud SQL.

- Compute & Containers : Compute Engine, Kubernetes Engine (GKE).

- Experience with CI/CD tools (e.g., Jenkins, GitHub, Bitbucket).

- Proficiency in Docker and Kubernetes for containerization and orchestration.

- Solid experience with Infrastructure as Code (IaC) tools like Terraform or Ansible.

- Familiarity with workflow orchestration tools such as Apache Airflow or Cloud Composer.

- Strong understanding of Agile/Scrum methodologies.

Nice-to-Have Skills :

- Experience with other cloud platforms (AWS, Azure).

- Knowledge of data visualization tools (e.g., Power BI, Looker, Tableau).

- Understanding of machine learning workflows and their integration with data pipelines.

Soft Skills :

- Strong problem-solving and critical-thinking abilities to tackle complex architectural challenges.

- Excellent communication skills to effectively collaborate with both technical teams and non-technical business stakeholders.

- A proactive, innovative, and continuous learning mindset.

- Ability to work independently while also excelling in a collaborative team environment.