Apply for AWS Data Engineer Job

6 to 8 Years Relevant Experience

We are seeking a highly skilled and experienced Senior AWS Data Engineer to join our data engineering team. The ideal candidate will have a strong background in building modern data platforms on AWS, with hands-on experience in data lakes, data warehouses, orchestration tools, data quality frameworks, and CI/CD pipelines. This role will play a key part in designing scalable, secure, and efficient data solutions that support advanced analytics and data governance.

Key Responsibilities

• Design, develop, and maintain scalable data lake architectures on AWS using S3, Glue Data Catalog, Glue Jobs, and Apache Hudi for efficient storage and processing.
• Build and manage data ingestion, transformation, and ETL pipelines using AWS Glue and integrate with downstream analytics tools such as Amazon Athena and Redshift Spectrum.
• Architect and implement data warehouse solutions using Amazon Redshift Serverless, focusing on performance, cost-efficiency, and data accessibility.
• Implement data access control and governance using Lake Formation, IAM, Secrets Manager, and Secret Server, ensuring data security and compliance.
• Automate and orchestrate workflows using Apache Airflow (MWAA), ensuring robust scheduling, monitoring, and logging of data pipeline executions.
• Apply data quality frameworks using AWS Glue Data Quality to ensure completeness, accuracy, and integrity of data across systems.
• Set up and maintain CI/CD pipelines using GitHub and GitHub Actions, enabling continuous integration and deployment of data engineering solutions.
• Collaborate with data scientists, analysts, and business stakeholders to understand data requirements and deliver reliable, scalable solutions.
• Monitor and optimize performance across data pipelines and queries, implementing best practices in partitioning, schema design, and lifecycle policies.

Required Skills & Experience

• 6–8 years of professional experience in data engineering, with at least 3+ years on AWS.
• Deep expertise in AWS Glue, S3, Glue Data Catalog, Glue Data Quality, and Athena.
• Hands-on experience with Amazon Redshift (Serverless & Spectrum) and data modeling for analytics.
• Strong understanding of data governance and access control using Lake Formation, IAM, and Secrets Manager.
• Proficient in building and managing data workflows with Apache Airflow (MWAA).
• Solid experience with Python and SQL for data transformation and scripting.
• Experience using version control systems (GitHub) and automating deployments via GitHub Actions.
• Familiarity with Hudi for managing large-scale transactional data in data lakes.
• Excellent problem-solving skills with a focus on performance tuning and optimization.
• Strong communication and collaboration skills, with the ability to work across teams and manage stakeholders effectively.

Preferred Qualifications

• AWS certification (e.g., AWS Certified Data Analytics, Solutions Architect) is a plus.
• Experience with data cataloging and lineage tools.
• Exposure to DevOps, monitoring tools (e.g., CloudWatch), and cost optimization techniques in AWS.
• Experience in real-time or near real-time data streaming is advantageous.