Description

Job Responsibilities include:

Design and implement scalable Lakehouse architecture (Bronze, Silver, Gold layers) to support enterprise data and AI use cases.

Build and optimize data pipelines, ETL/ELT processes, and streaming/event-driven architectures across diverse data sources.

Enable Data-as-a-Service by developing reusable data products, APIs, and integration frameworks.

Lead implementation of AI/GenAI solutions, supporting real-time analytics and advanced business insights.

Collaborate with stakeholders to translate business needs into scalable data and AI architecture solutions.

Ensure data governance, quality, and compliance by integrating cataloging tools and best practices into architecture.

Required Qualifications:

Bachelor’s or master’s degree in computer science, Data Engineering, Information Systems, or a related field.

10+ years of experience in data architecture, data engineering, or enterprise data platforms.

Strong expertise in modern data architectures (Lakehouse, ETL/ELT, streaming) with hands-on experience in cloud platforms such as Google Cloud (BigQuery, Cloud Storage).

Proven experience implementing AI/GenAI solutions, building scalable data pipelines, and embedding data governance using tools like Collibra, Alation, or Informatica

Key Skills

Education

Any Graduate