Data Engineer(Python and Databricks)

As a Data Engineer at TRINETIX, your main responsibilities include developing and maintaining web applications using Python, focusing on AI/LLM integration. You'll collaborate with cross-functional teams to design new features, troubleshoot software issues, and optimize applications for performance and scalability. Regular code reviews and mentoring other team members will also be part of your workflow, ensuring a collaborative environment for quality coding.

To qualify for the Data Engineer role at TRINETIX, candidates should have at least 2 years of experience with Python and a minimum of 1 year working with Databricks. Familiarity with frameworks such as Pandas and NumPy, as well as cloud knowledge of Azure, AWS, or GCP, is desired. Additionally, you should have skills in Spark, SQL, and Delta Lake, along with a solid understanding of machine learning concepts.

Data Engineers at TRINETIX will engage with a variety of technologies, including Databricks for data processing and management, Spark for big data solutions, and machine learning technologies like OpenAI’s GPT family. You'll also work with NoSQL databases, cloud services (Azure, AWS, GCP), and ETL systems, allowing for a rich experience across innovative projects.

TRINETIX offers a comprehensive benefits package for its Data Engineers, including medical insurance, sports program compensation, paid training programs, and language courses. Moreover, our flexible working hours allow for a balanced work-life dynamic, and we host team events and knowledge-sharing opportunities to foster community and growth within our teams.

At TRINETIX, we prioritize professional development and growth for our Data Engineers. Opportunities include access to cutting-edge projects in AI, mentorship programs, and participation in training courses. Our dynamic work environment encourages team collaboration and innovation, setting the stage for a fulfilling career path within the tech industry.

When discussing your Python experience during the interview for the Data Engineer position at TRINETIX, focus on specific projects where you developed applications or data pipelines. Share insights on libraries you've utilized, like Pandas or NumPy, and describe how your Python skills contributed to optimizing performance or solving complex data challenges.

In your response, highlight a systematic approach to troubleshooting, such as identifying the root cause before implementing solutions. Use scenarios from past experiences where you effectively diagnosed and resolved issues in data-driven applications, and emphasize methods you employed to prevent similar issues in the future.

When asked about Databricks in your interview, elaborate on specific projects you've worked on. Discuss how you utilized Databricks ML Flow, managed big data processing tasks, and collaborated with teams to build AI-driven solutions. Providing detailed examples will showcase your expertise and relevance to the Data Engineer role at TRINETIX.

In answering this question, discuss your understanding of core machine learning concepts, including model training and evaluation. Mention how you've incorporated ML techniques in past projects, specifically in relation to AI and LLM technologies. Highlight your understanding of the importance of data validation and preprocessing as well.

Explain techniques such as minimizing data redundancy, using efficient data storage solutions, and applying transformation methods to streamline data flow. Share past examples where your optimization efforts improved performance metrics or processing times, proving your capability in building robust data pipelines as a Data Engineer.

Select a complex project where you faced significant challenges, such as working with large datasets or integrating multiple technologies. Describe the problem, your approach to solving it, and the outcome. This allows you to demonstrate critical thinking and problem-solving skills relevant to the Data Engineer role at TRINETIX.

Discuss your practices around writing clean, maintainable code, such as following established coding standards, conducting thorough code reviews, and utilizing unit testing. Share how you promote peer review among team members and encourage a culture of high-quality code in your role as a Data Engineer.

When discussing your cloud experience, specify which platforms you've worked with and in what capacity. Highlight instances where you implemented cloud solutions for data storage or processing, discussing any specific projects that demonstrate your understanding of cloud technologies in the context of data engineering.

Discuss your experience with agile methodologies, particularly Scrum or Kanban, and explain how these frameworks benefit the development process at TRINETIX. Provide examples of how you adapt to changing requirements and work collaboratively in an agile team to deliver impactful solutions as a Data Engineer.

Share your genuine enthusiasm for the intersection of data engineering and AI, emphasizing how the innovative projects at TRINETIX align with your professional goals. Discuss the dynamic team environment and potential for influence within the role, showcasing your motivations for wanting to contribute to our exciting projects.