Job Description :

We are looking for an experienced Data Engineer with 4 - 5 years of hands-on experience in designing, developing, and maintaining scalable data pipelines and data platforms. The ideal candidate should have strong technical expertise along with excellent communication skills and experience working directly with US customers/stakeholders.

Key Responsibilities :

- Design, develop, and maintain scalable ETL/ELT data pipelines.

- Build and optimize data pipelines using Python, Apache Spark, Airflow, and AWS Glue.

- Work with MongoDB and other source systems to extract, transform, and load data into data warehouse/lake environments.

- Implement data integration and Change Data Capture (CDC) processes.

- Develop and optimize data warehouse models, including star schema and dimensional models.

- Work with modern Data Lake architectures, including Apache Iceberg.

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

- Collaborate directly with US customers and stakeholders to understand requirements and resolve data-related issues.

- Participate in customer calls and clearly communicate technical solutions, challenges, and project status.

- Work closely with Product, Engineering, Analytics, and Customer-facing teams.

- Ensure data accuracy, validation, reliability, and proper documentation.

- Contribute to the continuous improvement of data architecture and engineering practices.

- Effectively use AI-assisted development tools while validating outputs for accuracy, security, and business requirements.

Must-Have Skills :

- 4 to 5 years of professional experience in Data Engineering.

- Strong hands-on experience with Python.

- Experience with Apache Spark and distributed data processing.

- Experience with Apache Airflow or similar workflow orchestration tools.

- Hands-on experience with AWS Glue and AWS data services.

- Strong experience working with MongoDB or similar databases.

- Good understanding of ETL/ELT pipelines and data integration.

- Experience with Data Warehousing, Star Schema, and Dimensional Modeling.

- Knowledge of Data Lake architecture and Apache Iceberg is preferred.

- Experience with CDC (Change Data Capture) is highly desirable.

- Strong SQL skills and experience with data transformation and optimization.

- Good understanding of data quality, validation, monitoring, and troubleshooting.

Customer-Facing Experience :

- Prior experience working directly with US customers/stakeholders is mandatory.

- Excellent verbal and written English communication skills.

- Must be comfortable leading or actively participating in customer-facing calls.

- Ability to understand customer requirements and translate them into technical solutions.

- Ability to explain complex technical concepts clearly to both technical and non-technical stakeholders.

- Strong confidence in handling customer questions, discussions, and issue resolution independently.

Benefits :

- Competitive compensation

- Opportunity to work on modern data technologies

- Exposure to AI-driven FinTech and mortgage analytics

- Direct interaction with US customers and stakeholders

- Opportunity to work with a modern cloud data stack

- Collaborative and growth-oriented work environment