Cloud Engineer (Data/AI)

We are looking for Cloud Engineer (Data/AI) to design, build, and maintain scalable data pipelines that power our analytics and AI initiatives. You'll own the full lifecycle - from infrastructure and orchestration to transformation and delivery - working across AWS-native services (Glue, Lambda, Redshift) and Snowflake to build enterprise-grade data platforms. You'll contribute to our platform's technical strategy and mentor engineers on the team. Key Responsibilities: Design and implement data pipelines using Airflow and Kafka, ensuring reliability, idempotency, and failure handling Build and optimize data transformations in Snowflake and dbt; design schema architecture and data models Develop AWS Glue jobs and Lambda functions for ETL/ELT workflows; integrate with Redshift and Snowflake Write production Python and SQL; manage infrastructure-as-code (Terraform) on AWS Optimize for cost and performance; conduct code reviews and establish best practices Mentor junior engineers and partner with data analysts, BI engineers, and ML teams to define data requirements and SLAs Required Qualifications: 4+ years building data pipelines in production (Python, SQL, at least one orchestration tool) Strong AWS fundamentals (EC2, S3, IAM, compute services); hands-on with Glue and Lambda Snowflake architecture, performance optimization, and SQL development Experience with dbt or similar transformation frameworks Hands-on with Terraform. Distributed processing with PySpark or Spark SQL Nice to Have: Event streaming platforms (Kafka, Kinesis) Amazon Redshift design and optimization; Quick dashboard development Data quality frameworks, testing, and monitoring CI/CD and GitHub Actions; Coaching or mentoring experience; knowledge of data governance and security