Data Engineer

Role Overview

As a Data Engineer at Sundayy/Aristocrat, you will design, build, and optimize data pipelines and infrastructure to support analytics, reporting, and business intelligence. You’ll partner with data scientists, analysts, and product teams to deliver reliable, scalable data systems for data-driven decision-making.

Responsibilities

• Design, build, and maintain scalable data pipelines (extract → transform → load) into data warehouses or analytics platforms.
• Develop reliable and maintainable data processing workflows in Python and Node.js.
• Develop and optimize data models aligned to business domains and analytical use cases.
• Use ETL orchestration tools (e.g., Apache Airflow or Prefect) to schedule, monitor, and manage production workflows.
• Optimize queries and processing logic for large volumes of transactional data.
• Implement data validation, testing, and observability to ensure integrity and reliability.
• Troubleshoot data quality issues, pipeline failures, and performance bottlenecks.
• Collaborate with stakeholders to gather requirements and deliver solutions.
• Document pipelines, models, and technical decisions for maintainability.

Requirements

• 4+ years of professional experience in data engineering (or closely related).
• Strong SQL skills and experience with data modeling for analytics/reporting.
• Proficiency in Python and Node.js for pipeline development.
• Hands-on experience with ETL orchestration tools such as Apache Airflow or Prefect.
• Solid understanding of ETL/ELT, data pipeline architecture, and scalable best practices.
• Familiarity with Linux/Unix for deployment/operations.
• Ability to work independently and make sound technical decisions.
• Strong attention to data quality, validation, and testing.
• Excellent communication skills with non-technical stakeholders.

Nice to Have

• Experience with graph databases such as Neo4j.