Data Engineer

Overview This is a full-time work from home opportunity for a Data Engineer from LATAM. IDT ( is an American telecommunications company founded in 1990 and headquartered in New Jersey. It is a leading provider of prepaid communication and payment services and one of the world’s largest international voice carriers. We are listed on the NYSE, with over 1300 employees across 20+ countries and revenues in excess of $1.5 billion. IDT is seeking a skilled Data Engineer to join our BI team and contribute to data analysis, ELT/ETL design and support to deliver on strategic initiatives. Responsibilities Design, implement, and validate ETL/ELT data pipelines—for batch processing, streaming integrations, and data warehousing—while maintaining documentation and testing to ensure reliability and accuracy. Maintain end-to-end Snowflake data warehouse deployments and develop Denodo data virtualization solutions. Recommend process improvements to increase efficiency and reliability in ELT/ETL development. Stay current on emerging data technologies and support pilot projects, ensuring the platform scales with growing data volumes. Architect, implement, and maintain scalable data pipelines that ingest, transform, and deliver data into real-time data warehouse platforms, ensuring data integrity and pipeline reliability. Partner with data stakeholders to gather requirements for language-model initiatives and translate into scalable solutions. Create and maintain comprehensive documentation for all data processes, workflows and model deployment routines. Stay informed and learn emerging methodologies in data engineering and open-source technologies. Requirements 5+ years of experience in ETL/ELT design and development, integrating data from heterogeneous OLTP systems and API solutions, and building scalable data warehouse solutions to support business intelligence and analytics. Excellent English communication skills; effective oral and written communication with BI team and user community. Demonstrated experience in utilizing Python for data engineering tasks, including transformation and large-scale data processing. Design and implement event-driven pipelines using messaging and streaming events to trigger ETL workflows and enable scalable, decoupled data architectures. Experience in data analysis, root cause analysis, and problem-solving. Experience designing complex data pipelines extracting data from RDBMS, JSON, API and flat file sources. Expertise in SQL and PL/SQL, with hands-on experience in relational databases and cloud services (e.g., Oracle, MySQL, Amazon RDS, Snowflake, Amazon Redshift). Proven ability to analyze and optimize poorly performing queries and ETL/ELT mappings, with performance tuning recommendations. Understanding of software engineering principles and experience with Unix/Linux/Windows, and Agile methodologies. Proficiency in version control and working in distributed development environments. Interest in business operations and understanding of how robust BI systems drive profitability through data-driven decision-making. Pluses Experience developing ETL/ELT processes within Snowflake and complex transformations using built-in SQL capabilities. Experience with Pentaho Data Integration (Kettle) or Ab Initio ETL tools. Experience designing and implementing cloud-based ETL solutions using Azure Data Factory, DBT, AWS Glue, Lambda, and open-source tools. Experience with reporting/visualization tools (e.g., Looker) and job scheduler software. Experience in Telecom, eCommerce, International Mobile Top-up. Preferred certifications: AWS Solutions Architect, AWS Cloud Data Engineer, Snowflake SnowPro Core. Please attach CV in English. The interview process will be conducted in English. Only accepting applicants from LATAM. #J-18808-Ljbffr