Google Cloud Data Engineer

Vation Digital Pvt. Ltd.; Bengaluru; On-site; INR 1,500,000 - 2,000,000; Full time

Job summary

A leading digital solutions provider based in Bangalore is looking for a seasoned Google Cloud Data Engineer. The ideal candidate will have over 6 years of experience in data engineering, specializing in Google Cloud services like Vertex AI and BigQuery. Responsibilities include designing scalable data pipelines, implementing ML workflows, and integrating AI models into production. Strong expertise in Google Cloud Platform, SQL, and Python is required, alongside a passion for leveraging AI technologies for business impact.

Qualifications

• 6+ years of experience in data engineering or data platform development.
• 2+ years in the Google Cloud environment.
• Strong hands-on expertise in Vertex AI.

Responsibilities

• Design and build scalable data pipelines using Google Cloud services.
• Implement end-to-end ML workflows on Vertex AI.
• Integrate AI/ML models into production systems using MLOps best practices.
• Monitor model performance and drift.

Skills

Google Cloud Platform (GCP)

Vertex AI

SQL

Python

Apache Beam/Spark

Data governance

MLOps best practices

Feature engineering

Tools

BigQuery

Dataflow

Pub/Sub

Dataproc

Cloud Storage

Cloud Composer

Job description

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:

• 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.