Data Engineer (Talend) - Remote

As a Data Engineer (Talend) at Aperia Solutions, your primary responsibilities include designing, developing, testing, and deploying new ETL pipelines or enhancing existing ones. You will also perform application development and maintain software applications while providing production support. This role involves translating functional requirements into technical designs and automating ETL processes for various datasets in our big data platform.

To succeed as a Data Engineer (Talend) at Aperia Solutions, candidates should have 5+ years of IT experience and at least 1 year of development experience using the Talend Data Integration module. Strong knowledge of Java programming, PL-SQL, and experience with Hadoop, Hive, and various databases is essential. Additionally, familiarity with API integration, Unix/Linux, and CI/CD practices will be advantageous.

Candidates interested in the Data Engineer (Talend) role at Aperia Solutions should possess a minimum of 5 years of IT experience, along with specific experience in Talend Data Integration. Knowledge in database management, data modeling, and cloud technologies related to Big Data are also valuable. Previous experience in the finance or banking industry can be a plus.

The Data Engineer (Talend) position at Aperia Solutions follows a Monday to Friday work schedule, allowing for a balanced work-life setup. Being a remote position based in Vietnam, you can work from the comfort of your home while contributing to the company's success.

As a Data Engineer (Talend) at Aperia Solutions, you can look forward to a range of benefits that include health and dental insurance, paid time off, and parental leave. Additionally, childcare assistance is available, highlighting our commitment to supporting our employees both in and out of the workplace.

When answering this question, be specific about your previous roles where you've used Talend. Discuss specific projects you worked on, the challenges you faced, and how you overcame them, ensuring to highlight how your contributions led to successful outcomes.

Discuss the techniques you use for performance tuning and optimization, such as minimizing data movement, proper indexing, and utilizing parallel processing. Mention any specific metrics you track to evaluate the pipelines’ performance and any tools you use to assist in this.

Prepare a strong example that showcases your problem-solving skills. Outline the context, the specific data issue you faced, the steps you took to investigate and address the problem, and the final outcome. Be sure to highlight any positive impacts on the business or the team.

Explain your approach to API integration, including any tools and methods you prefer. Discuss how you ensure data security, handle authentication, and how you manage errors that may arise during the integration process.

Discuss your exposure to big data technologies such as Hadoop, Hive, and related tools. Share specific instances where you applied these technologies in your previous work and how they contributed to the success of projects.

Outline your process for understanding functional requirements, such as collaborating with stakeholders or utilizing requirement gathering techniques. Mention how you document those requirements and translate them into actionable technical designs.

Highlight your approach to maintaining data quality, including validation processes, data cleansing techniques, and ensuring accuracy in ETL processes. Discuss specific tools or methods you employ to uphold data integrity.

Explain your familiarity with GitLab or similar version control systems, detailing how you use them for code management, collaboration, and tracking changes. Share examples of best practices you follow when working in a team environment.

Detail any experience you have with Continuous Integration and Continuous Deployment. Discuss how you've applied these practices in past projects, the tools used, and how they helped streamline processes and improve the code quality.

Stay current on emerging technologies and trends in cloud computing related to Big Data. Share what you are exploring, how you stay informed through resources or networks, and any applications or projects where you are considering applying these new technologies.