Job Title: GCP Data Engineer - AI Focus
Role Overview: Seeking a highly motivated GCP Data Engineer to join our Innovation and Platform Architecture team. The candidate will play a crucial role in building and operating cloud-native data pipelines and AI-enabled applications on Google Cloud Platform, spanning the ingestion, transformation, and retrieval of enterprise data for both analytics and generative AI use cases. The ideal candidate should be proactive, detail-oriented, and capable of collaborating with stakeholders to ensure project success.
Key Responsibilities:- Deliver solutions that enable operational and business users to access trusted data and AI-driven insights.
- Design, build, and maintain end-to-end data pipelines on Google Cloud Platform, landing data in Google Cloud Storage and modeling it in BigQuery across layered raw, refined, and curated datasets.
- Develop and support AI and retrieval-augmented generation solutions using Vertex AI, including embedding generation, vector search, and grounding against enterprise document and structured data sources.
- Build and deploy containerized services and APIs on Cloud Run, publishing and versioning images through Artifact Registry.
- Orchestrate and schedule pipeline execution using Cloud Workflows and Cloud Scheduler, including monitoring, retry logic, and error handling.
- Develop transformation logic and data quality assertions in Dataform or equivalent SQL transformation frameworks.
- Follow best practices for governance, security, lifecycle management, and data protection, including least-privilege Cloud IAM design and service account management, ensuring compliance with enterprise standards.
- Collaborate with stakeholders to gather requirements and translate them into technical specifications and data models.
- Evaluate and recommend tools, technologies, and platforms to enhance productivity and achieve business outcomes.
- Stay current with the latest trends and advancements in the cloud data and AI space.
- Demonstrate continuous learning and growth while gradually assuming increased ownership and responsibility.
Required Qualifications:- 2+ years of hands-on experience engineering data solutions on Google Cloud Platform.
- Hands-on experience with BigQuery, including SQL development, partitioning and clustering, and cost-aware query design.
- Hands-on experience with Vertex AI for building, deploying, or consuming machine learning and generative AI capabilities.
- Experience with Google Cloud Storage, including bucket organization, lifecycle policies, and structured data landing patterns.
- Working knowledge of Cloud IAM, including roles, service accounts, and least-privilege access design.
- Experience deploying and operating containerized services on Cloud Run.
- Proficiency in SQL and Python.
- Excellent problem-solving and critical-thinking skills.
- Strong communication skills with the ability to translate user needs into technical solutions.
- Ability to work independently, manage priorities, and operate with high self-sufficiency.
- A dedicated work ethic and commitment to delivering high-quality results.
Preferred Qualifications (Nice-to-Haves):- Experience with Dataform for managing SQL transformation workflows, dependency graphs, and data quality assertions.
- Experience orchestrating and scheduling pipelines with Cloud Workflows and Cloud Scheduler.
- Experience managing container images and artifacts in Artifact Registry.
- Familiarity with BigQuery Agents and the BigQuery Conversational API, or comparable natural-language-to-data interfaces.
- Familiarity with retrieval-augmented generation patterns, including document parsing, chunking strategies, and vector search.
- Experience integrating cloud data platforms with enterprise source systems such as ERP, scheduling, or document repositories.
- Experience working within Agile/Scrum development methodologies.
- Google Cloud Professional Data Engineer or Professional Machine Learning Engineer certification.
Work Location: Remote
