Job Title

Hands-on Data Engineer who is comfortable working with modern AWS data services, partnering with business stakeholders, and supporting production reporting workloads. Will design, build, and support data pipelines and analytics datasets. This role focuses on ingesting data from corporate systems, organizing it in a cloud-based data lake, and enabling reliable reporting. Key Responsibilities Design, build, and maintain scalable data ingestion frameworks using AWS native services (e.g., Glue, Lambda, S3, Step Functions) and SnapLogic to data into the data lake. Architect and manage the enterprise data lake on Amazon S3 using Apache Iceberg, including partitioning strategies, schema evolution, metadata optimization, and lifecycle management. Develop robust data transformation pipelines (ELT/ETL) to standardize, cleanse, and enrich source system data for downstream analytics and operational use cases. Develop and maintain reporting-ready views and queries using Amazon Athena and AWS Glue metadata. Implement and monitor data quality frameworks, including validation rules, reconciliation checks, and anomaly detection to ensure integrity and reliability of enterprise data asset Qualifications required : Bachelor’s degree in Computer Science, Engineering, Information Systems, or equivalent experience. 7 years of experience in data engineering. Advanced English Strong SQL skills and experience building analytical datasets for reporting. Hands-on experience with AWS data platforms, including S3, Athena, Glue, AWS Unified Catalog. Experience integrating data from SaaS or enterprise systems using ETL tools such as SnapLogic Experience supporting BI tools such as Amazon QuickSight, Tableau, or Power BI.