Data Engineer

Talend ETL/ELT Developer – Snowflake

Industry: Travel & Transportation
Duration: 12 Months
Work Arrangement: Remote

Required Skills (Maximum 6)

1. Talend ETL/ELT Development – Strong experience developing, maintaining, and optimizing ETL/ELT pipelines using Talend.

2. Snowflake – Hands-on experience with Snowflake, modern data warehousing, and cloud-based data engineering.

3. SQL & Performance Optimization – Strong SQL skills, including complex queries, troubleshooting, and query performance tuning.

4. Data Modeling & Integration – Experience with data modeling, integrating multiple data sources, and processing structured and semi-structured data.

5. Data Quality & Pipeline Reliability – Experience implementing data validation, monitoring pipelines, troubleshooting failures, and ensuring data accuracy and reliability.

6. Communication & Documentation – Strong communication skills and the ability to document technical solutions, data workflows, and processes.

Nice-to-Have Skills (Maximum 3)

1. Azure Data Engineering Tools – Experience with Azure Data Factory, Azure Databricks, and Azure DevOps.

2. CI/CD & Development Tools – Familiarity with CI/CD pipelines, version control, dbt, and data governance practices.

3. Talend & Snowflake Platforms – Experience with Talend Studio, Talend Management Console, and Snowflake Snowsight.
   
   Key Responsibilities

4. Design, develop, maintain, and optimize ETL/ELT data pipelines using Talend to support enterprise data integration and transformation requirements.

5. Develop and optimize complex SQL queries and Snowflake data processing workflows to ensure high performance and scalability.

6. Build and maintain modern cloud-based data warehouse solutions, integrating structured and semi-structured data from multiple sources.

7. Develop and maintain data models, transformation logic, and data integration processes to support business reporting and analytics.

8. Implement data quality checks, validation rules, and monitoring mechanisms to ensure data accuracy, consistency, and reliability.

9. Monitor pipeline performance, troubleshoot data processing failures, perform root cause analysis, and implement corrective actions.

10. Collaborate with data engineers, architects, analysts, and business stakeholders to understand requirements and deliver effective data solutions.

11. Use Azure DevOps, CI/CD pipelines, and version control tools to manage code changes, deployments, and development workflows.

12. Maintain technical documentation covering data pipelines, source-to-target mappings, transformation logic, and operational procedures.

13. Follow data governance, security, and development best practices to ensure reliable and maintainable data engineering solutions.

For immediate consideration please click APPLY to begin the screening process with Alex.