Data Engineer Manager

Job Description - Design and optimize scalable, cost-efficient end-to-end data architectures. - Improve data delivery speed and engineering efficiency year over year. - Build reusable frameworks, templates, and automation to reduce repetitive work. - Develop and maintain reliable data pipelines, real-time systems, and analytics platforms. - Deliver production-ready solutions under tight timelines without compromising quality. - Resolve complex production issues independently and implement long-term fixes. - Evaluate new tools, frameworks, and architectures with clear cost–benefit analysis. - Proactively reduce technical debt and prevent recurring scalability issues. - Make and communicate technical trade-offs (e.g., batch vs. streaming, build vs. buy). - Apply advanced data or analytics concepts in production systems. - Act as a technical authority through code reviews, design reviews, and best practices. - Collaborate with stakeholders and translate technical decisions into business impact. Qualifications - Bachelor’s degree in Computer Science, Engineering, Data Science, or a related field. - Minimum 3 years of experience in data engineering or related roles. - Strong experience building and operating production-scale data systems. - Hands-on experience with data pipelines, data warehouses/lakes, and cloud platforms. - Solid understanding of batch and streaming data processing. - Experience supporting analytics, machine learning, or AI data workflows. - Strong problem-solving skills in complex production environments. - Strong judgment in balancing speed, quality, cost, and scalability. - Clear communication skills with both technical and non-technical stakeholders.