ACN I&P - GN - SONG - AI & Data - Marketing - MMM GCP - Manager

Job Title - Data Engineering Consultant - GCP Architecture | S&C

Management Level: 07 - Manager

Location: PAN India

Must Have Skills: GCP Architecture (BigQuery, Dataflow, Pub/Sub, Vertex AI Pipelines, Gemini API Integration), PySpark, SQL, Apache Beam

Good to Have Skills: dbt, Airflow, Terraform, Python

Job Summary:

As a Data Engineering Consultant specializing in GCP Architecture, you will be responsible for designing, building, and optimizing cloud-native data solutions on Google Cloud Platform. Your typical day will involve architecting scalable data pipelines using BigQuery, Dataflow, and Pub/Sub, integrating generative AI capabilities via the Gemini API, and deploying ML workflows through Vertex AI Pipelines. You will work closely with data architects and engineering teams to translate business requirements into production-grade GCP data architectures and deliver robust GCP solutions.

Roles & Responsibilities:

• Design and implement end-to-end data architectures on GCP leveraging BigQuery, Dataflow, Pub/Sub, Vertex AI Pipelines, and Gemini API.
• Build scalable, serverless streaming and batch data pipelines using Apache Beam and Cloud Dataflow.
• Integrate Gemini API for generative AI use cases within data products and analytical workflows.
• Orchestrate ML training and inference pipelines on Vertex AI, ensuring reliability and performance at scale.
• Configure real-time event-driven architectures using Pub/Sub for data ingestion and messaging.
• Collaborate with data scientists, analysts, and client stakeholders to define data platform requirements.
• Conduct performance tuning, cost optimization, and governance reviews for GCP environments.
• Stay current with GCP product releases and AI/ML advancements, recommending adoption where impactful.
  
  

Professional & Technical Skills:

• Must Have Skills: Proficiency in GCP services — BigQuery, Dataflow, Pub/Sub, Vertex AI Pipelines, and Gemini API Integration, hands-on experience in Pyspark, SQL, Python for pipeline development.
• Hands-on experience designing and deploying streaming and batch data pipelines on GCP.
• Strong SQL and Python skills for data transformation and pipeline development.
• Experience with Vertex AI Pipelines for orchestrating end-to-end ML workflows.
• Knowledge of IAM, VPC, and GCP security best practices for data platforms.
• Familiarity with CI/CD tooling and infrastructure-as-code (Terraform or Deployment Manager).
• Exposure to dbt or similar transformation frameworks is an advantage.
  
  

Additional Information:

• The ideal candidate will have a strong background in cloud data engineering with demonstrable experience delivering GCP-based solutions in consulting or enterprise environments.
• This position is based at PAN India offices.
  
  

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