Key Responsibilities:

- Design, develop and maintain scalable data pipelines using Azure Databricks and Snowflake.

- Build and optimize ETL/ELT workflows for large-scale data processing.

- Work with Azure Data Factory, Azure Data Lake Storage and related Azure services.

- Develop efficient data models and optimize SQL queries for performance.

- Integrate GenAI and LLM capabilities into data engineering workflows.

- Collaborate with data scientists, AI engineers and business stakeholders.

- Ensure data quality, security, governance and reliability.

- Monitor pipeline performance and troubleshoot data processing issues.

Required Skills:

- 6 - 8 years of experience in Data Engineering.

- Strong hands-on experience with Azure Databricks and Snowflake.

- Proficiency in Python, PySpark and SQL.

- Experience developing ETL/ELT pipelines and working with cloud data platforms.

- Knowledge of Azure Data Factory and Azure Data Lake Storage.

- Understanding of data warehousing, data modelling and performance optimization.

- Exposure to Generative AI, LLMs, RAG or AI-integrated data workflows.

- Strong analytical, problem-solving and communication skills.