Principal Engineer

We are seeking a highly skilled and experienced Principal Engineer in Data Analytics to lead and solution provider to accelerate digital transformation. At this position, you will be responsible for overseeing the end-to-end data engineering lifecycle, from data acquisition and storage to processing and analysis. You will collaborate closely with cross-functional teams, including data scientists, software engineers, and business stakeholders, to understand data requirements and develop robust data solutions that support our business objectives.

• Lead the design, development, and implementation of scalable data pipelines and ETL processes to collect, transform, and load data from various sources into our data ecosystem.
• Collaborate with business stakeholders to understand their data analysis needs and translate them into clear and actionable research questions and objectives
• Build and maintain interactive dashboards and data visualization tools to communicate findings and insights to senior management and stakeholders.
• Design and develop data visualization to have an easy way to access the data and monitor the line
• Collaborate with data scientists to deploy machine learning models into production environments and integrate them with data pipelines for real-time inference and batch processing
• Explore the data to find efficiency improvement opportunities and co-work with business owner to realize in line
• Drive innovation in data analysis techniques and methodologies, staying abreast of industry trends and emerging technologies

Requirements

• Bachelor's Degree or higher in Computer Science, IT , Engineering or equivalent fields.
• At least 5-7 years of relevant experience.
• Advanced working SQL knowledge and experience working with relational databases, query authoring (SQL) as well as working familiarity with a variety of databases and big data platforms, esp. MySQL, PostgreSQL and MSSQL.
• Proficiency in programming languages such as Python, Java, or Scala, with a strong emphasis on writing clean, maintainable, and efficient code.
• Strong problem-solving skills and analytical thinking, with the ability to troubleshoot complex data issues and optimize performance.
• Excellent communication and collaboration skills, with the ability to effectively interact with technical and non-technical stakeholders.
• Hands-on experience with big data technologies and frameworks, including Hadoop, Spark, Kafka, and Hive is a PLUS.
• Preferred: Experience with containerization and orchestration technologies such as Docker and Kubernetes