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Vation Digital

Google Cloud Data Engineer

Hybrid, with primary location as Bangalore

Experience Level:

6+ years of experience in data engineering or data platform development, with at least 2+ years in the Google Cloud environment.

Role Overview:

We are looking for an experienced Google Cloud Data Engineer with strong hands-on expertise in Vertex AI and the Google Cloud AI ecosystem. The ideal candidate will design and implement scalable data pipelines, enable ML workflows, and collaborate with AI/ML engineers and data scientists to operationalize data-driven solutions.

Key Responsibilities:

  • Design and build scalable data pipelines using Google Cloud services such as BigQuery, Dataflow, Dataproc, Pub/Sub, and Cloud Storage.
  • Implement end-to-end ML workflows on Vertex AI — covering data preparation, feature engineering, model training, tuning, deployment, and monitoring.
  • Integrate AI/ML models into production systems using MLOps best practices.
  • Work with BigQuery ML, Vertex AI Workbench, and AI APIs (Vision, NLP, Speech, Translation, Generative AI) to build intelligent, data-driven solutions.
  • Build and maintain data orchestration pipelines using Cloud Composer / Airflow and automate retraining using Cloud Build or GitHub Actions.
  • Ensure data pipelines meet requirements for performance, security, governance, and lineage.
  • Monitor model performance and drift, ensuring timely retraining and optimization.
  • Partner with cross-functional teams to design data architectures that support both analytics and AI use cases.
  • Evaluate emerging tools and techniques in the Google AI stack (e.g., Gemini, Vertex AI Agent Builder, RAG, LangChain integrations) to enhance the platform’s intelligence layer.

Required Skills & Experience:

  • Strong expertise in Google Cloud Platform (GCP) services — including BigQuery, Dataflow, Pub/Sub, Dataproc, Cloud Storage, and Cloud Composer.
  • Hands-on experience with Vertex AI for model training, hyperparameter tuning, deployment, and monitoring.
  • Knowledge of Google AI/ML APIs (Vision, Natural Language, Speech, Translation, Generative AI models).
  • Proficiency in SQL, Python, and Apache Beam/Spark for data engineering.
  • Understanding of feature engineering, model versioning, and data lineage within ML pipelines.
  • Familiarity with CI/CD pipelines for ML (MLOps best practices).
  • Experience integrating structured and unstructured data sources.
  • Knowledge of data governance, IAM, and security in GCP.

Nice-to-Have:

  • Google Cloud Certified: Professional Data Engineer or Machine Learning Engineer.
  • Experience with RAG (Retrieval-Augmented Generation) solutions and LLM fine-tuning on Vertex AI.
  • Familiarity with Looker, Data Studio, or other visualization tools.
  • Experience in cross-functional collaboration with AI research and product engineering teams.

Soft Skills

  • Excellent problem-solving and analytical abilities.
  • Strong communication and stakeholder management skills.
  • Passion for leveraging AI and cloud technologies to deliver measurable business impact.