Google Data Engineer
Job Description: Join our dynamic Data & AI practice as a Google Data Engineer, where you’ll be delivering high impact client-facing data transformation initiatives across industries.
As a Google Data Engineer you will be responsible for designing, developing, and managing data and AI solutions on the Google Cloud Platform. You will be responsible for creating data pipelines, managing ETL/ELT processes, optimising data storage and retrieval, designing scalable data architectures, and integrating generative AI capabilities using Vertex AI and Gemini. You’ll have the opportunity to leverage the latest tools to enable our clients with modern, AI-ready Data Platforms.
Our Google Cloud practice continues to grow from strength to strength, delivering cutting-edge cloud and AI transformation programmes across industries. We are embedding Gen AI — including Vertex AI and Gemini — into the solutions we deliver for our clients, and in how we deliver them, making Accenture’s Data & AI team a fantastic place to make an impact and grow your career.
Project Description / Key Responsibilities:
- Designing and building Data Products on GCP using services such as BigQuery, Cloud Storage, Dataflow, Dataplex, and Looker.
- Data Pipeline Development using Cloud Dataflow (Apache Beam), Cloud Composer (Apache Airflow), Pub/Sub, and Datastream for change data capture.
- Data Modelling and Mapping aligned to business requirements and cloud-native best practices on BigQuery.
- Integration of Vertex AI and Gemini capabilities into data and AI solutions, including RAG pipelines, Gemini API calls, and Vertex AI Agent Builder workflows.
- Leveraging data engineering tools like dbt for transformation and data quality on BigQuery.
- Performance Optimisation of GCP data services including BigQuery slot management, partitioning and clustering strategies, and Dataflow pipeline tuning.
- Programming and Data Modelling using Python, SQL, and GCP SDKs (google-cloud libraries).
Key Skills:
- Highly proficient in SQL programming for writing complex queries to extract, manipulate, and analyse data from BigQuery, including use of BigQuery ML for in-database model development.
- Proficiency in Python for data engineering, automation, and integration with GCP services via google-cloud libraries and Apache Beam; experience with Java or Scala is a plus.
- Hands-on experience with Vertex AI and Gemini, including invoking Gemini APIs, building RAG applications with Vertex AI Search and Vector Search, and integrating Vertex AI into data pipelines and applications.
- Minimum 5+ years in Data Engineering and Data Warehousing, with demonstrated experience on GCP.
- Expertise in ETL/ELT processes and tools, including Cloud Dataflow, dbt, Cloud Composer (Airflow), and Datastream.
- Experience with infrastructure-as-code (Terraform preferred) and GitOps
- Good communication skills and ability to learn quickly.
Location: Melbourne, Sydney, Brisbane, Canberra
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Sydney
Brisbane
Canberra
Melbourne
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