AWS Data Engineer

Job Description

We are seeking a highly skilled and motivated AWS Certified Engineer to design, build, and optimize scalable data solutions within the Amazon Web Services (AWS) ecosystem. The ideal candidate will have strong expertise in big data processing using PySpark and a deep understanding of data warehousing concepts, including Hive and modern table formats such as Iceberg. This role involves developing, deploying, and managing robust, efficient, and secure data pipelines and analytics solutions on AWS, leveraging core networking and compute services.

AWS Certified Data Engineer

• Design, develop, and deploy scalable and cost‑effective data solutions on AWS, leveraging services such as S3 (for data lakes), EC2, EMR, Glue, Athena, Lambda, Redshift, and Kinesis.
• Build and maintain robust ETL/ELT data pipelines using PySpark for data ingestion, transformation, and loading into various data stores, including those utilizing open table formats like Iceberg.
• Develop and optimize big data processing jobs using PySpark on AWS EMR or AWS Glue, handling large datasets efficiently and integrating with Iceberg table formats.
• Design, implement, and manage data warehousing solutions, including schema design, data modeling, and query optimization, focusing on Hive and modern data lake table formats like Iceberg for historical data and analytical queries.
• Implement secure and robust cloud infrastructure components, including VPCs, subnets, routing, and security groups, to ensure proper connectivity and isolation for data solutions.
• Design, deploy, and manage containerized data processing applications on Amazon Elastic Kubernetes Service (EKS).
• Optimize AWS resources and big data applications (Spark, Hive, Iceberg) for performance, cost, and efficiency.
• Implement best practices for data security, access control, and compliance within AWS, including IAM policies, S3 bucket policies, and encryption.
• Set up monitoring, alerting, and logging for data pipelines and AWS infrastructure; troubleshoot and resolve issues promptly.
• Develop and maintain automation scripts using Python and shell scripting for infrastructure provisioning, deployment, and operational tasks.
• Work closely with data scientists, analysts, and other engineering teams to understand data requirements and deliver reliable data solutions.

• Hold at least one AWS certification (e.g., AWS Certified Solutions Architect – Associate, AWS Certified Data Analytics – Specialty, AWS Certified Developer – Associate).
• Hands‑on experience with key AWS services for data processing and storage, including S3, EC2, EMR, Glue, Athena, Lambda, VPC, subnets, routing, security groups, and EKS.
• Strong proficiency in PySpark for developing complex data transformations and analytics.
• Practical experience with Apache Iceberg for managing and querying data lakes.
• In‑depth knowledge and practical experience with Apache Hive for data storage, querying, and schema management.
• Expert‑level proficiency in Python (Boto3, scripting, data manipulation).
• Proficient in shell scripting for automation and operational tasks.
• Strong SQL skills for data querying and manipulation.
• Solid understanding of ETL/ELT processes, data modeling, distributed computing, and data governance.
• Bachelor of Computer Science.

• Experience with Kubernetes for deploying and managing containerized applications.
• Experience with CI/CD tools and practices (e.g., AWS Code Pipeline, Git Hub Actions, Git Lab CI).
• Experience with workflow orchestration tools like Apache Airflow.
• Proficient using Git for source code management.
• Exposure to other big data technologies such as Apache Kafka, Flink, or Presto.

• AWS Certified Solutions Architect – Associate/Professional
• AWS Certified Data Analytics – Specialty
• AWS Certified Developer – Associate

Salary Range: $125,000 to $140,000 per year