Senior Data Engineer

The Company:  Our client is a dynamic and innovative organization with a strong focus on global collaboration and excellence in delivering advanced solutions.

We are seeking a Senior Data Engineer to build and enhance a scalable data ecosystem that supports analytics and decision-making across complex, multi-regional operations. This role focuses on ensuring high-quality, reliable, and accessible data by developing robust pipelines, integrating diverse data sources, and enabling analytics teams with well-structured datasets.

Key Responsibilities:

1. Data Engineering & Architecture

• Design, develop, and maintain data pipelines (ETL/ELT) across various internal and external systems.
• Build and manage structured data layers to support efficient transformation, storage, and analytics consumption.
• Define and implement scalable data models, including schema design and performance optimization strategies.
• Collaborate with technology teams to ensure seamless integration across enterprise systems and platforms.

2. Data Quality & Governance

• Establish and monitor data validation frameworks to ensure data accuracy and consistency.
• Manage data platform performance, reliability, and cost efficiency.
• Maintain clear documentation of data assets, lineage, and transformation logic.
• Support governance initiatives, including metadata management and data standardization.

3. Cross-functional Collaboration

• Work closely with analytics, data science, and business stakeholders to deliver high-value datasets.
• Translate business requirements into technical data solutions and specifications.
• Communicate technical concepts clearly to non-technical audiences.

4. Optimization & Continuous Improvement

• Drive automation and efficiency improvements across data workflows.
• Continuously enhance data pipeline performance and scalability.
• Evaluate and adopt modern tools, frameworks, and best practices in data engineering.
• Mentor junior team members and promote best practices in development and documentation.

Requirement:

• Degree in Computer Science, Data Engineering, Information Systems, or a related field.

• Proven experience in data engineering or data platform development within a complex business environment.

• Strong track record of delivering scalable data solutions that support analytics and reporting.

• Hands-on experience with modern data architectures and large-scale data processing.

• Experience working in data-intensive environments with multiple data sources is preferred.

• Proficiency in SQL, Python, and data pipeline development.

• Experience with modern data platforms and tools (cloud-based environments preferred).

• Strong understanding of data modeling and scalable architecture patterns.