GCP Data Architect

Role and Responsibilities

• Act as a key Cloud Data Engineer for enterprise engagements.

• Work closely with the Lead Data Consultant to deliver data platform solutions.

• Define high-level solution architecture and detailed technical designs for cloud-based data platforms, primarily on GCP.

• Develop and implement solutions through hands-on coding and configuration.

• Collaborate with data engineering teams to provide technical guidance on architecture, design decisions, and implementation approaches.

• Conduct pair-programming sessions with data engineers and support knowledge transfer of the developed solutions.

• Contribute to the successful transition and handover of solutions to engineering teams.

Minimum Qualifications

Solution Architecture & Technical Expertise

• Strong experience designing cloud data platform architectures, including:

  • Migrating existing open-source or public-cloud data platforms to GCP or other cloud environments.

  • Designing and implementing greenfield data platforms from the ground up.

• Ability to research emerging tools and technologies, assess their suitability, identify key architectural considerations, and recommend appropriate technology choices.

• Experience defining architecture and detailed technical designs for:

  • Batch data ingestion and processing from files, cloud platforms, and on-premises databases.

  • Real-time and streaming data ingestion and processing, including log analytics, clickstream analytics, and other event-driven use cases.

• Hands-on experience developing data pipelines and CI/CD pipelines.

• Strong understanding of at least one major public cloud platform, with GCP being preferred.

Cloud & Technology Experience

• Strong hands-on experience with GCP or equivalent services on other public cloud platforms.

• Experience with technologies such as:

  • Google Cloud Dataflow

  • Google Cloud Pub/Sub

  • Cloud Composer

  • BigQuery

  • Cloud Run

  • Cloud Functions

  • Cloud Spanner

  • Cloud Build

  • Vertex AI

  • Terraform

Programming Skills

• Strong programming fundamentals with a willingness to remain hands-on in day-to-day engineering activities.

• Proficiency in at least one of the following, preferably both:

  • Python

  • Java

Preferred Qualifications

Data Engineering & Architecture

• Experience working with open-source data ecosystems and distributions such as:

  • Hadoop

  • Apache Spark

  • Cloudera

  • Hortonworks

• Knowledge of NoSQL technologies such as:

  • HBase

  • MongoDB

Additional Technology Experience

• Exposure to other public cloud platforms such as AWS or Azure.

• Experience with open-source frameworks and technologies including:

  • Hadoop

  • Spark

  • Oozie

  • Kafka

  • HBase

Certifications

At least one relevant cloud certification, preferably:

• Google Cloud Professional Data Engineer

• AWS certification

Enterprise Experience

• Experience working within large-scale enterprise environments.

• Strong understanding of architectural governance, design review, and approval processes.

• Ability to prepare and present architecture/design submissions and work effectively with cross-functional stakeholders.

• Experience collaborating with architecture, engineering, security, infrastructure, and business teams in complex enterprise environments.