Associate Technical Architect

Experience

We are seeking a highly skilled Data Engineer to design, develop, and maintain robust data pipelines and AI-driven data products on Google Cloud Platform (GCP).

The ideal candidate will have expertise in BigQuery, Python, and cloud-native tools, along with hands-on experience in machine learning, retrieval-augmented generation (RAG), and data governance.

You will play a key role in supporting scalable, secure, and intelligent data systems that power business insights and AI applications.

Must Have Skills

• 10+ years of experience in

  data engineering

  , with at least 4+ years on

  Google Cloud Platform

  .
• Strong programming skills in

  Python

  and experience with cloud-based data engineering.
• Hands-on experience with GCP, especially BigQuery, Dataflow, Cloud Composer, and Cloud Functions.
• Familiarity with Vertex AI, BigQuery ML, Dialogflow, and

  AI model deployment

  .
• Proficient in building and maintaining ETL/ELT pipelines.
• Experience with CI/CD practices and tools in data workflows.
• Knowledge of retrieval-augmented generation (RAG), vector databases/search, prompt engineering is a plus.
• Solid understanding of data governance, privacy, and compliance standards.
• Strong SQL skills with a focus on BigQuery SQL.
• Experience with Spark or distributed data processing frameworks. (Good to have)
• Comfortable with API development, webhooks, and using tools like Postman.
• Excellent communication and documentation skills.

Good to have skills

• Familiarity with other Cloud technologies
• Working experience on JIRA and Agile
• Stakeholder communication
• Microsoft Office
• Cross functional team work internally and with external clients
• Team Lead
• Requirement gathering

Key Responsibilities:

• Data Pipeline Development:
• Build and optimize scalable ETL/ELT data pipelines using Dataflow, Cloud Composer, and BigQuery.
• Cloud Infrastructure:
• Design and deploy data solutions on Google Cloud Platform (GCP), utilizing services like Cloud Functions, Vertex AI, BigQuery, and GCS.
• Data Management:
• Ensure high data quality, governance, and privacy compliance across all stages of the data lifecycle.
• API Development:
• Design and consume APIs for data interaction and AI integration; use tools like Postman to test and document.
• Collaboration:
• Work closely with cross-functional teams, including data science, product, engineering, and compliance.
• AI & ML Integration:
• Collaborate with data scientists and ML engineers to deploy models using Vertex AI, support BigQuery ML, and integrate sentiment analysis and prompt engineering workflows.
• Conversational AI & RAG Systems:
• Support development of intelligent applications using Dialogflow, webhooks, vector search, and retrieval-augmented generation methods.
• Automation & CI/CD:
• Develop and manage CI/CD pipelines for data engineering workflows, ensuring reliability and reproducibility.
• Performance & Optimization:
• Optimize BigQuery SQL and Spark processes for cost and speed efficiency in handling large datasets.

Certification:

• GCP Professional Data Engineer/Architect Certification.
• Snowflake Associate / Core