ETL Engineer

📋 Description

• • As an ETL Engineer at EazyML, you will play a critical role in building and maintaining robust data pipelines that transform raw data into actionable insights, enabling data-driven decision-making across the organization. Your work will directly impact the reliability, scalability, and performance of the company’s data infrastructure, supporting analytics, machine learning models, and business intelligence initiatives.
• • You will design, develop, and optimize ETL (Extract, Transform, Load) processes using modern data engineering tools and frameworks, ensuring data quality, consistency, and timeliness from diverse sources into data warehouses and lakes. This includes writing complex SQL queries, developing Python-based transformation scripts, and orchestrating workflows with tools like Apache Airflow or similar schedulers.
• • Day-to-day responsibilities include monitoring pipeline performance, troubleshooting failures, implementing data validation checks, and collaborating with data scientists, analysts, and software engineers to understand data requirements and deliver reliable datasets for reporting and modeling.
• • You will contribute to the evolution of the data platform by adopting best practices in data modeling (star/snowflake schemas), implementing incremental loading strategies, and ensuring compliance with data governance and security standards.
• • The engineering team at EazyML is a collaborative, innovation-driven group focused on building scalable software solutions in the MLops and AI infrastructure space. You’ll work closely with cross-functional teams in a remote-first environment that values autonomy, technical excellence, and continuous learning.
• • This role offers significant growth opportunities to deepen your expertise in cloud-based data engineering (AWS/GCP/Azure), real-time data streaming (Kafka, Kinesis), and modern data stack technologies, positioning you as a key contributor to the company’s data platform evolution and enabling impact at scale.