AWS Data Engineer
- Design and develop data architecture: Create scalable, reliable, and efficient data lakehouse solutions on AWS, leveraging Apache Iceberg and other AWS services for table formats.
- Build and maintain data pipelines: Design, construct, and automate ETL/ELT processes to ingest data from diverse sources into the AWS ecosystem.
- Create and manage data APIs: Design, develop, and maintain secure and scalable RESTful and other APIs to facilitate data access for internal teams and applications, typically leveraging AWS services.
- Implement AWS services: Utilize a wide array of AWS tools for data processing, storage, and analytics, such as Amazon S3, Amazon EMR, and AWS Lake Formation, with native Iceberg support.
- Manage Iceberg tables: Build and manage Apache Iceberg tables on Amazon S3 to enable data lakehouse features like ACID transactions, time travel, and schema evolution.
- Optimize data performance: Implement partitioning strategies, data compaction, and fine-tuning techniques for Iceberg tables to enhance query performance.
- Ensure data quality and integrity: Implement data validation and error-handling processes, leveraging Iceberg's transactional capabilities for consistent data.
- Ensure security and compliance: Implement robust data security measures, access controls, and compliance with data protection regulations, including using AWS Lake Formation with Iceberg and implementing authorization on APIs via IAM or Cognito.
- Collaborate with stakeholders: Work closely with data scientists, analysts, software engineers, and business teams to understand their data needs and deliver effective solutions.
- Provide technical support: Offer technical expertise and troubleshooting for data-related issues related to pipelines and API endpoints.
- Maintain documentation: Create and maintain technical documentation for data workflows, processes, and API specifications.
- Qualifications
- Education: Bachelor's degree in Computer Science, Information Technology, or a related field.
- Experience: Proven experience in data engineering, with significant hands-on experience using AWS cloud services.
- Technical skills:
- Programming : Proficiency in programming languages like Python, Java, or Scala.
- SQL: Strong SQL skills for querying, data modeling, and database design.
- AWS Services: Expertise in relevant AWS services such as S3, EMR, Lambda, API Gateway, SageMaker and IAM.
- Apache Iceberg: Hands-on experience building and managing Apache Iceberg tables.
- Big Data: Experience with big data technologies like Apache Spark and Hadoop.
- API Development: Experience creating and deploying RESTful APIs, with knowledge of best practices for performance and security.
- ETL/Workflow: Experience with ETL tools and workflow orchestration tools like Apache Airflow.
- DevOps: Familiarity with DevOps practices, CI/CD pipelines, and infrastructure as code (Terraform) is often desired.
- Soft skills:
- Strong problem-solving and analytical skills.
- Excellent communication and collaboration skills.
- Ability to work independently and as part of an agile team.
- Certifications (Preferred):
- AWS Certified Data Analytics
- AWS Certified Data Engineer
- Specialty or other relevant AWS certifications.
#LI-
#DI- Ref: #208-Rowland Tulsa
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