Middle Data Engineer (AWS)

• Design, develop, and maintain robust ETL/ELT pipelines to extract, transform, and load data from multiple disparate sources into centralized data warehouse environments.
• Build and support data warehouse infrastructure to drive analytics, reporting, and operational visibility for business stakeholders.
• Ensure high data readiness, accuracy, and reliability by implementing rigorous validation, testing, and transformation logic.
• Integrate diverse datasets to deliver comprehensive, analytics-ready data models tailored to specific business requirements.
• Monitor production data pipelines proactively, troubleshooting and resolving data flow issues to maintain system continuity and performance.
• Document data flows, ETL architecture, and data structures to support long-term maintainability and seamless knowledge transfer.
• Collaborate closely with cross-functional teams and clients to translate business needs into scalable, efficient data solutions.

Qualifications

• Hold a minimum Bachelor’s degree (S1) in Computer Science, Information Technology, Information Systems, or a related quantitative field.
• Bring around 3 years of professional hands-on experience working as a Data Engineer or in a similar data-focused engineering role.
• Strong, demonstrable expertise in ETL/ELT development, data warehouse architecture, and data modeling best practices.
• Hands-on professional experience utilizing cloud data services and infrastructure, specifically within AWS (e.g., AWS Glue, S3, RDS, or related data stack components).
• Core technical proficiency in Python, Advanced SQL, and modern transformation frameworks like dbt.
• Experience working with relational databases (such as Postgres) and business intelligence/visualization tools (such as Looker Studio or Power BI).
• Familiarity with Agile workflows and collaboration tools like Jira.
• Strong analytical, problem-solving, and communication skills with the ability to manage stakeholder expectations effectively.