Technical Lead

Business Title

Data Engineer

Years of Experience

Min 6 and max upto 10.

Job Descreption

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

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

1. Familiarity with other Cloud technologies
2. Working experience on JIRA and Agile 3. Stakeholder communication 4. Microsoft Office 5. Cross functional team work internally and with external clients 6. Team Lead 7. Requirement gathering

Key responsibiltes

Must Have
- 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. Good to have
- 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.

Education Qulification

1. Bachelor s or Master Degree or equivalent Degree
Certification If Any

1. GCP Professional Data Engineer/Architect Certification.
2. Snowflake Associate / Core

Shift timing

12 PM to 9 PM and / or 2 PM to 11 PM - IST time zone

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