AWS Data Engineer

About the Role

We are seeking a highly skilled Data Engineer to design, build, and optimize scalable data pipelines and lakehouse solutions on AWS. The ideal candidate will have strong experience in enterprise-scale data engineering, ETL development, and modern cloud-based data platforms. This role will be responsible for building and maintaining Medallion Architecture (Bronze, Silver, Gold) data pipelines to support analytics, reporting, and business intelligence initiatives.

Key Responsibilities

• Design, develop, and maintain AWS-based data pipelines following Medallion Architecture (Bronze, Silver, Gold).
• Build and optimize ETL/ELT workflows using AWS Glue, Spark, and Python.
• Develop and manage data ingestion pipelines using AWS DMS and Kinesis.
• Implement data transformation and enrichment processes to support analytics and reporting requirements.
• Integrate data solutions with AWS Athena, Redshift, and other downstream data consumers.
• Create and maintain datasets using Parquet and Apache Iceberg formats.
• Ensure data quality, consistency, governance, and lineage across the data platform.
• Implement monitoring, logging, and alerting mechanisms to maintain pipeline reliability.
• Collaborate with Data Architects, Data Analysts, and Business Stakeholders to understand data requirements and deliver scalable solutions.
• Participate in CI/CD implementation and automation for ETL deployment and maintenance.
• Support data cataloging, governance, and security initiatives using AWS Lake Formation and/or DataZone.

Required Qualifications

• 5+ years of experience in Data Engineering.
• Proven experience building enterprise-scale ETL/ELT and Lakehouse solutions.
• Experience handling large-scale data processing and analytics workloads.
• Strong understanding of data modeling, performance optimization, and data quality practices.
• Strong hands-on experience with AWS Glue, AWS DMS (Database Migration Service), AWS Kinesis, Amazon Athena,Amazon Redshift,Apache Spark / PySpark,Python, SQL
• Experience working with Parquet, Apache Iceberg, Data Lake and Lakehouse architectures
• Knowledge of Git version control and CI/CD pipelines for data engineering workflows.
• Experience with data governance, metadata management, and cataloging tools such as AWS Lake Formation and AWS DataZone.

Preferred Qualifications

• AWS Certified Data Analytics Specialty.
• AWS Certified Solutions Architect.
• Experience with modern data platform modernization initiatives.
• Exposure to Agile/Scrum development methodologies.

Disclaimer: This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.