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,
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 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.
