Data Engineer

Responsibilities:

• Design, implement, and validate ETL/ELT data pipelines–for batch processing, streaming integrations, and data warehousing, while maintaining comprehensive 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 seamlessly 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.
• Should be willing to 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 skills with BI team and user community.
• Demonstrated experience in utilizing python for data engineering tasks, including transformation, advanced data manipulation, and large-scale data processing.
• Design and implement event-driven pipelines that leverage messaging and streaming events to trigger ETL workflows and enable scalable, decoupled data architectures.
• Experience in data analysis, root cause analysis and proven problem solving and analytical thinking capabilities.
• Experience designing complex data pipelines extracting data from RDBMS, JSON, API and Flat file sources.
• Demonstrated expertise in SQL and PLSQL programming, with advanced mastery in Business Intelligence and data warehouse methodologies, along with hands-on experience in one or more relational database systems and cloud-based database services such as Oracle, MySQL, Amazon RDS, Snowflake, Amazon Redshift, etc.
• Proven ability to analyze and optimize poorly performing queries and ETL/ELT mappings, providing actionable recommendations for performance tuning.
• Understanding of software engineering principles and skills working on Unix/Linux/Windows Operating systems, and experience with Agile methodologies.
• Proficiency in version control systems, with experience in managing code repositories, branching, merging, and collaborating within a distributed development environment.
• Interest in business operations and comprehensive understanding of how robust BI systems drive corporate profitability by enabling data-driven decision-making and strategic insights.

Pluses

• Experience in developing ETL/ELT processes within Snowflake and implementing complex data transformations using built-in functions and SQL capabilities.
• Experience using Pentaho Data Integration (Kettle) / Ab Initio ETL tools for designing, developing, and optimizing data integration workflows.
• 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 Certification: AWS Solution Architect, AWS Cloud Data Engineer, Snowflake SnowPro Core.

Please attach CV in English.

Originally posted on Himalayas