- Data Architecture & Development : Lead the design, development, and optimization of scalable, secure, and high-performance data solutions in Databricks.

- ETL/ELT Pipeline Engineering : Build and maintain robust pipelines, integrating Databricks with Azure Data Factory (or AWS Glue), ensuring reliability and efficiency.

- Advanced Analytics & AI Integration : Implement machine learning models and Generative AI-powered solutions to deliver business innovation.

- Collaboration : Partner with data scientists, analysts, and business teams to translate requirements into technical designs and deliverables.

- Data Quality & Governance : Enforce best practices for data validation, governance, and security to ensure trust and compliance.

Technical Leadership : Mentor junior engineers, conduct code reviews, and foster a culture of continuous learning.

Innovation & Research : Stay current with the latest trends in Databricks, Azure Data Factory, cloud platforms, and AI/ML to recommend and implement improvements.

Required Qualifications :

- Bachelors or masters degree in computer science, Information Technology, or a related field.

- 5+ years in data engineering, with at least 3 years of hands-on experience in Databricks.

- Proven expertise in :

1. Data modelling, Data Lakehouse architectures, and ELT/ETL processes

2. SQL and at least one programming language (Python or Scala)

- Integration with Azure Data Factory or AWS Glue

- Strong understanding of cloud platforms (Azure preferred) and containerization (Docker).

- Excellent analytical, problem-solving, and communication skills.

- Demonstrated experience mentoring or leading technical team

Preferred Skills :

- Experience with Generative AI technologies and their applications.