About the Role :

We are looking for an experienced Azure Data Engineer with strong hands-on expertise in Azure Data Factory, Snowflake, DBT, SQL and Python. The candidate will be responsible for designing, developing and optimizing scalable ETL/ELT data pipelines and cloud data solutions.

Key Responsibilities :

- Design, develop and maintain scalable ETL/ELT pipelines using Azure Data Factory (ADF).

- Build and manage data ingestion and integration pipelines into Snowflake.

- Develop and maintain DBT models, transformations, tests and data-quality checks.

- Write complex and optimized SQL queries for data transformation, validation and performance improvement.

- Use Python for data processing, automation and pipeline-related development.

- Monitor, troubleshoot and optimize data pipelines for reliability and performance.

- Work with business stakeholders and analysts to understand requirements and translate them into technical solutions.

- Implement data quality, validation, governance and documentation standards.

- Participate in code reviews, deployment activities and production support.

- Collaborate with Data Architects, Analysts, DevOps and other engineering teams.

Mandatory Skills :

- Azure Data Factory (ADF)

- Snowflake

- DBT (Data Build Tool)

- SQL

- Python

Good to Have :

- Azure Data Lake Storage Gen2 (ADLS), Azure Synapse Analytics, Azure Functions, Databricks / PySpark, CI/CD and Azure DevOps, Data Governance, Power BI / Tableau, DataStage / Netezza, Insurance domain experience.

Candidate Requirements :

- Minimum 5 - 10 years of overall Data Engineering experience.

- Strong hands-on experience in Azure data engineering and cloud-based data platforms.

- Experience designing and supporting production-grade ETL/ELT pipelines.

- Strong analytical and problem-solving skills.

- Good communication and stakeholder-management skills.