Job
Description
Job Title: AWS Data Engineer Job Summary We are looking for a skilled Data Engineer to join our team and help build, deploy, and maintain data pipelines and data systems using AWS technologies. In this role, you will be responsible for designing and implementing data integration processes, ensuring data quality, and providing technical expertise in data modeling, ETL, and business intelligence. You will work collaboratively with cross-functional teams to support a range of data-driven projects and initiatives. Responsibilities Data Pipeline Development: Design, develop, test, and deploy data integration processes using AWS services (e.g., Redshift, RDS, Glue, S3, Lambda, Kinesis, Step Function) and other tools. Data Integration: Build and manage data pipelines for batch and real-time data processing. Develop and maintain data models to support business needs and ensure data accuracy. Documentation: Create and maintain technical documentation, including ETL architecture, data integration specifications, and data testing plans. Collaboration: Work with business users and stakeholders to understand data requirements, create data flows, and develop conceptual, logical, and physical data models. Technology Utilization: Leverage AWS technologies and best practices to optimize data processing and integration. Stay current with emerging technologies and recommend innovative solutions. Data Quality: Ensure the accuracy, reliability, and performance of data systems. Implement testing strategies and automation to maintain data integrity. Support & Maintenance: Provide support for data systems and pipelines, troubleshooting and resolving issues as they arise. Perform regular maintenance and updates to ensure optimal performance. Reporting & Analytics: Collaborate with the reporting team to design and implement data solutions that support business intelligence and analytics. Required Qualifications Experience: 4+ years of hands-on experience as a Data Engineer with a strong focus on AWS technologies (e.g., EMR, Redshift, RDS, Glue, S3, Lambda, Athena, Kinesis & Cloud Watch). Technical Skills: Proficient in Python and SQL script creation, and data integration tools. Experience with data modeling and ETL processes. Programming Skills: Experience in programming languages such as Python, PySpark, or Scala. Database Platforms: Experience with major database platforms (e.g., SQL Server, Oracle, Snowflake, Redshift). Orchestration & Automation: Familiarity with orchestration tools (e.g., AWS Data Pipeline, Step Functions), infrastructure automation (e.g. Terraform, CloudFormation) and CI/CD pipelines (e.g. Jenkins, GitLab CI/CD). Build & Test Tools: Working knowledge of build tools (e.g., Maven, Gradle) and testing frameworks (e.g., JUnit, pytest). Documentation: Ability to create comprehensive technical documentation and maintain clear records of data processes and systems. Education: Bachelor’s degree in Computer Science, Information Systems, or a related field. Preferred Skills & Experience Big Data Frameworks: Experience with big data frameworks (e.g., Spark, Hadoop) and related technologies (e.g., pySpark, SparkSQL). Data Integration Processes: Knowledge of data warehousing, data integration, and ETL processes. Communication: Strong communication skills, with the ability to effectively collaborate with team members and stakeholders. Problem-Solving: Demonstrated ability to troubleshoot complex data issues and implement effective solutions. Agile Environment: Experience working in an agile development environment with tools like Azure DevOps or JIRA. If you are a motivated data professional with experience in AWS and a passion for solving complex data challenges, we encourage you to apply for this exciting opportunity. Show more Show less
