Lead a team of data engineers, providing technical guidance, mentoring, and fostering a collaborative environment.
Design and develop scalable data pipelines and ETL processes to extract, transform, and load large volumes of data from various sources and based on the requirements of accuracy, timeliness, reliability, and scalability.
Build and maintain analytics tools that utilize the data pipeline to provide actionable insights into operational efficiency and other key business performance metrics.
Build and maintain automation tools to optimize operational performance and minimize manual labor.
Architect and maintain data infrastructure, ensuring data quality, reliability, and security.
Work closely with project managers, data analysts & other engineers to turn data into information that can be used to make sound business decisions and deliver efficient solutions.
Implement and optimize data models and schemas to support data analytics and reporting needs.
Define and enforce data engineering best practices, coding standards, documentation guidelines, and implement best practices for data management, including data quality, data security, and data privacy.
Being responsible for the full life cycle development, implementation, support of self-serve data products.
Stay updated with emerging technologies and industry trends, recommending and implementing innovative solutions to improve data engineering practices.
Requirements
Master's or Bachelor's degree in Computer Science/Information Systems or any related fields.
3+ years of relevant experiences working in data engineering or related fields. Previous working experiences in a credit or financial company will be a strong plus.
Proficiency in working with big data technologies, such as Hadoop, Spark, or Kafka.
Experience with cloud platforms like AWS, Azure, or GCP, and familiarity with related services such as S3, Redshift, or BigQuery.
Strong programming skills in languages such as Python and Scala, along with expertise in SQL.
Experience working in a UNIX environment is preferred.
Proficient in Software Development Life Cycle (SDLC) including code version control, test driven development, and technical documentation.
Solid software engineering skills with experience in scripting, APIs, and computational automation.
Ability to translate complex technical concepts to non-technical stakeholders.
Excellent problem-solving skills with the ability to troubleshoot and resolve data-related issues.
Comfortable working with a variety of languages, frameworks, and technologies, adapting to the most suitable tool for the task at hand.
Demonstrated leadership abilities, with experience leading and mentoring a team of data engineers.
Knowledge of data governance, data security, and compliance standards is a strong plus.
