Role Overview
The Data Engineer is responsible for designing, building, and maintaining scalable data pipelines, databases, and processing systems that support analytics, reporting, and business intelligence. This role focuses on ensuring that data is accurate, accessible, reliable, and efficiently processed across various platforms. Data Engineers collaborate closely with data analysts, data scientists, and software teams to deliver robust infrastructure that enables data-driven decision-making. Ideal candidates are detail-oriented, technically strong, and capable of solving complex data challenges in fast-paced environments.
Key Responsibilities
* Design, develop, and maintain data pipelines, ETL/ELT workflows, and integration processes across multiple data sources.
* Build and optimize scalable data models, warehouses, and storage solutions for structured and unstructured datasets.
* Implement and manage data quality checks, validation rules, and monitoring mechanisms.
* Collaborate with analytics and data science teams to understand data requirements and deliver reliable datasets.
* Develop, maintain, and improve data infrastructure to support reporting, dashboards, and advanced analytics.
* Write efficient SQL queries, optimize database performance, and manage schema evolution.
* Work with cloud platforms, distributed systems, or big-data technologies to support large-scale processing.
* Automate data workflows and ensure high levels of reliability, security, and operational efficiency.
* Document data structures, processes, and architectural decisions for consistent knowledge sharing.
* Assist in troubleshooting data issues, debugging pipeline failures, and improving system resilience.
* Support the implementation of best practices in data governance, access control, and compliance.
* Contribute to the design and development of APIs or services for data access.
Qualifications and Requirements
* Bachelor's degree in Computer Science, Data Engineering, Information Systems, or a related technical field.
* 1–3 years of experience in data engineering, data pipeline development, or backend engineering.
* Strong proficiency in SQL and experience with relational or NoSQL databases.
* Experience with ETL tools, data integration platforms, or pipeline orchestration frameworks.
* Hands-on experience with cloud environments and their data services.
* Familiarity with programming languages such as Python, Java, or Scala for data processing.
* Understanding of data modeling, warehousing concepts, and distributed computing.
* Knowledge of big-data technologies or streaming platforms is a plus.
* Strong analytical and problem-solving abilities with attention to detail.
* Ability to collaborate across cross-functional teams and communicate technical concepts clearly.
* Solid understanding of version control, CI/CD workflows, and containerization concepts.
Summary
The Data Engineer plays a crucial role in building and supporting the data infrastructure that powers analytics, reporting, and data-driven insights. By developing reliable pipelines, optimizing storage solutions, and ensuring data quality, this role provides the foundation for scalable and effective data operations. It offers strong career growth opportunities toward positions such as Senior Data Engineer, Data Architect, or Analytics Engineering Lead.