Responsibilities

• Lead the design and development of data architecture, ensuring scalability, security, and alignment with business strategy.
• Oversee the collection, transformation, and integration of data from multiple internal and external sources.
• Conduct advanced research and troubleshooting to address complex business and technical problems.
• Design, build, and optimize data pipelines and ETL processes to handle large-scale and real-time data.
• Implement automation solutions to minimize manual intervention and improve data efficiency.
• Provide technical leadership and mentorship to junior engineers, ensuring best practices in coding, testing, and deployment.
• Collaborate with cross-functional stakeholders including Data Scientists, Analysts, and Business Leaders to deliver actionable insights.
• Evaluate and recommend new tools, frameworks, and technologies to enhance data engineering capabilities.

Job Specification

• Bachelor’s Degree in Information Technology, Computer Science, Statistics, Mathematics, Business, or a related field (Master’s Degree is a plus).
• Minimum of 5 years’ experience in data engineering, with at least 2 years in a senior or lead role.
• Proven expertise in the data analytics lifecycle, including business problem framing, KPI/metrics design, exploratory analysis, and presenting data insights.
• Strong hands-on experience with cloud platforms (AWS, GCP, Azure) and advanced programming skills in Python, Java, PySpark.
• Solid knowledge of data processing, ETL frameworks, data warehousing, and messaging queue systems (e.g., Kafka).
• Demonstrated experience in designing highly scalable, resilient, and secure data systems.