Data Engineer
Role details
Job location
Tech stack
Job description
As a Data Engineer at Company, you will design, build, and optimize scalable data pipelines across AWS cloud ecosystems. You will work with modern data platforms such as Snowflake using Python data pipelines. This role requires strong technical hands-on skills, problem solving ability, and the agility to operate in fast-paced delivery environments., Build and optimize ETL/ELT data pipelines using Snowflake, Python. Develop high performance transformations using Python, SnowSQL etc., Implement Snowflake ingestion and transformation, including Snowpipe, streams/tasks, and performance tuning. Manage large and complex datasets, ensuring reliability, quality, and reusability. Collaborate with data architects, analysts, and business teams to translate requirements into scalable data engineering solutions. Apply best practices for CI/CD, code versioning, testing, and deployment in cloud environments. Ensure compliance with security, governance, and data quality standards across pipelines. Support ongoing development, optimization, and maintenance of data platforms.
Requirements
Snowflake development: schema design, transformations, UDFs, query optimization. Strong SQL skills with experience on large-scale distributed datasets. Hands-on experience with AWS cloud platforms Experience with ETL orchestration frameworks (e.g., Redwood, Airflow). Ability to work with complex data models, metadata, and pipeline debugging. Understanding of data lakehouse architecture and modern data engineering patterns. Knowledge of CI/CD using Git, DevOps pipelines. Preferred / Good to Have: Understanding of ML lifecycle Understanding DBT experience/knowledge Soft Skills: Strong communication skills with ability to engage clients and stakeholders. Collaborative, proactive, and adaptable to global delivery models. Analytical mindset with problem-solving aptitude.