Responsibilities:

• Design and develop scalable, high-performance data pipelines ensuring integrity and efficiency.
• Collaborate with data scientists, analysts, and engineers to meet data requirements.
• Optimize data infrastructure and architecture for better performance and reliability.
• Implement and maintain ETL processes for large-scale data transformation.
• Develop and manage data models for accurate and accessible analytics.
• Conduct data validation and quality assurance to resolve inconsistencies.
• Troubleshoot pipeline failures, performance bottlenecks, and data issues.
• Stay updated on industry trends and best practices in data engineering.
• Lead and mentor data engineers, fostering a culture of innovation.
• Align data strategies with business goals and drive process improvements.

Requirements:

• Bachelor's or Master's degree in Computer Science, Engineering, or a related field.
• Experience: Minimum 8 years in data engineering, with a focus on building and optimizing data pipelines & infrastructure.
• Strong proficiency in Python & SQL, with the ability to write efficient, optimized code.
• In-depth knowledge of data modeling concepts and experience in implementing and maintaining data models.
• Solid understanding of ETL processes & frameworks, with hands-on experience designing and implementing ETL workflows.
• Experience with at least one ETL tool (IBM DataStage, Talend, or Informatica).
• Familiarity with data warehousing concepts and modeling techniques like dimensional modeling & data vault.