Data Engineer

Role Summary

The Data Engineer will be responsible for building, optimizing, and maintaining scalable data pipelines and cloud-based data platforms that support business analytics and operational decision-making. The role involves transforming complex raw datasets into reliable, high-quality data assets while ensuring scalability, performance, and system reliability across enterprise environments.

Key Responsibilities

• Design, develop, and maintain scalable batch and real-time data pipelines using modern data engineering frameworks.
• Build and optimize ETL/ELT workflows for consolidating data from ERP systems, project management tools, and operational platforms.
• Architect and manage AWS cloud-based data infrastructure including S3, RDS, and workflow orchestration tools.
• Develop efficient data models, data lake architectures, and optimized storage solutions for analytics and reporting.
• Ensure high availability, reliability, data quality, and integrity across operational and financial datasets.
• Monitor pipeline performance, troubleshoot failures, and implement proactive monitoring solutions.
• Collaborate with business, analytics, and engineering teams to support data-driven initiatives.
• Conduct Proof of Concepts (POCs) for emerging technologies and scalable architecture improvements.
• Optimize system performance, cost-efficiency, and long-term scalability of data platforms.
• Maintain technical documentation, standards, and best practices for data engineering processes.

Qualifications & Experience

• Bachelor's or Master's Degree in Computer Science, Software Engineering, or related quantitative field.
• 3–5+ years of hands-on experience in Data Engineering or related roles.
• Strong proficiency in Python and SQL.
• Hands-on experience with PySpark, dbt, AWS RDS, and AWS-based data pipelines.
• Experience with CDC frameworks and streaming technologies such as Debezium and Kafka.
• Familiarity with Apache Airflow and Docker/containerization technologies.
• Experience working with relational databases, data lakes, and analytical databases.
• Knowledge of open table formats such as Apache Iceberg and Delta Lake is an added advantage.
• Exposure to object storage technologies such as S3 or MinIO.
• Experience handling ERP, industrial, manufacturing, construction, engineering, or logistics datasets is preferred.
• Strong analytical, troubleshooting, and problem-solving skills.