Data Engineer (Snowflake & DBT)

About Kenexai: Kenexai delivers smart, data-driven solutions that empower businesses across industries. Our mission is to combine deep, domain-specific expertise with cutting-edge technology to drive meaningful impact. With a trusted team, consistent quality, and a growing global presence, we remain committed to delivering excellence while staying true to our core values: innovation, integrity, and client success. Be part of a team thats not just building solutions but shaping the future with intelligence. Role Overview: We are seeking a talented and motivated Data Engineer with hands-on experience in Snowflake and DBT Core to join our growing data team. The ideal candidate will play a critical role in designing, building, and maintaining robust, scalable, and high-performance data pipelines that support analytics, reporting, and business intelligence initiatives across the organization. This role involves working closely with data analysts, data scientists, and engineering teams to ensure data is accurate, reliable, and readily available. Key Responsibilities: Design, develop, and maintain end-to-end ETL/ELT pipelines using Snowflake and DBT Core.Build modular, scalable, and reusable data models in DBT following best practices, including version control, testing, and documentation.Work with AWS Data Services (S3, Glue, Redshift) to ingest, transform, and store large volumes of structured and unstructured data.Collaborate with teams to implement data validation and testing frameworks to ensure high-quality, trustworthy data.Orchestrate complex workflows and data pipelines using Airflow / Astro, ensuring efficient scheduling and monitoring.Deploy and manage pipelines in containerized environments using Docker and Kubernetes for scalability and reliability.Integrate streaming data using Kafka for real-time processing and analytics.Participate in CI/CD pipelines using Terraform to automate deployment, versioning, and environment management.Monitor and troubleshoot data pipelines to ensure performance, reliability, and availability, proactively addressing potential issues.Collaborate with cross-functional teams to understand business requirements and translate them into efficient data solutions.Stay updated with emerging technologies and industry best practices in data engineering, cloud platforms, and modern data architecture. Required Skills & Qualifications: 3+ years of experience in Data Engineering with strong expertise in Snowflake and DBT Core.Proficient in SQL and Python for data transformation, scripting, and analysis.Hands-on experience with AWS ecosystem including S3, Glue, and Redshift.Ability to work effectively in a fast-paced, collaborative environment with multiple stakeholders. About Kenexai: Kenexai delivers smart, data-driven solutions that empower businesses across industries. Our mission is to combine deep, domain-specific expertise with cutting-edge technology to drive meaningful impact. With a trusted team, consistent quality, and a growing global presence, we remain committed to delivering excellence while staying true to our core values: innovation, integrity, and client success. Be part of a team thats not just building solutions but shaping the future with intelligence. Role Overview: We are seeking a talented and motivated Data Engineer with hands-on experience in Snowflake and DBT Core to join our growing data team. The ideal candidate will play a critical role in designing, building, and maintaining robust, scalable, and high-performance data pipelines that support analytics, reporting, and business intelligence initiatives across the organization. This role involves working closely with data analysts, data scientists, and engineering teams to ensure data is accurate, reliable, and readily available. Key Responsibilities: Design, develop, and maintain end-to-end ETL/ELT pipelines using Snowflake and DBT Core.Build modular, scalable, and reusable data models in DBT following best practices, including version control, testing, and documentation.Work with AWS Data Services (S3, Glue, Redshift) to ingest, transform, and store large volumes of structured and unstructured data.Collaborate with teams to implement data validation and testing frameworks to ensure high-quality, trustworthy data.Orchestrate complex workflows and data pipelines using Airflow / Astro, ensuring efficient scheduling and monitoring.Deploy and manage pipelines in containerized environments using Docker and Kubernetes for scalability and reliability.Integrate streaming data using Kafka for real-time processing and analytics.Participate in CI/CD pipelines using Terraform to automate deployment, versioning, and environment management.Monitor and troubleshoot data pipelines to ensure performance, reliability, and availability, proactively addressing potential issues.Collaborate with cross-functional teams to understand business requirements and translate them into efficient data solutions