Data Platform Engineer

As a Data Platform Engineer at Lendable, you will be responsible for shaping and scaling our data infrastructure. Your key tasks will include developing new tools for product teams, managing and evolving solutions on AWS and Snowflake, onboarding new data sources, and ensuring the smooth running of data pipelines. Additionally, you’ll work on optimizing CI/CD pipelines, designing infrastructure as code, implementing security best practices, and troubleshooting production issues.

To be considered for the Data Platform Engineer position at Lendable, you should have strong software development skills, particularly in Python or similar languages. Solid engineering practices, experience with cloud services like AWS, knowledge of columnar databases such as Snowflake, and familiarity with Terraform for infrastructure as code are essential. Experience in data-intensive applications, CI/CD pipelines, and excellent communication skills are also highly valued.

At Lendable, we prioritize growth and development for our Data Platform Engineers by providing opportunities to work on challenging projects that have a real impact. You’ll be part of a supportive team environment that encourages collaboration and the sharing of ideas. We also offer a competitive compensation package, including equity, and a healthy work-life balance with flexible working options to ensure you can focus on your career while having time for your personal life.

In your role as a Data Platform Engineer at Lendable, you’ll work with a stack that includes AWS for cloud services, Snowflake for data storage, and Python for software development. Additionally, you’ll use Terraform for infrastructure as code, alongside various data ingestion tools and practices to ensure that our analytics capabilities are top-notch and capable of scaling with the business.

Lendable boasts a vibrant and inclusive company culture that emphasizes teamwork, innovation, and transparency. As a Data Platform Engineer, you’ll be part of a small, exceptional team that values your input and expertise. We celebrate success together and maintain a friendly environment where employees feel valued and empowered to make impactful decisions.

When answering this question, emphasize your direct experience with Python in data engineering tasks. Discuss specific projects where you utilized Python for data processing, automation, or building data pipelines. Highlight your understanding of libraries such as Pandas or NumPy, and how they were instrumental in providing solutions at previous positions.

To effectively answer this, discuss best practices such as implementing automated tests, using monitoring tools, and applying data validation checks. You can also share examples of when you encountered data quality issues and how you resolved them, showcasing your problem-solving skills.

In your response, mention specific AWS services you’ve worked with, such as S3, Lambda, or EC2, and describe how they contributed to your projects. You can provide details about deploying applications or setting up data pipelines and how AWS's scalability benefits projects.

When answering this question, outline your approach to CI/CD optimization, such as incorporating automation, parallel testing, and improving code review processes. Offer examples of how you've increased deployment speed or reliability in previous roles, which will illustrate your experience and problem-solving capabilities.

Share a specific instance where you faced a production issue, detailing the troubleshooting steps you took to identify the problem. Explain how you gathered logs, collaborated with team members, and implemented fixes. Emphasize your methodical approach and how the resolution improved overall system reliability.

In your response, detail the steps you took to successfully integrate a new data source. Outline the challenges you faced and how you addressed them. Discuss how you ensured that the data was properly ingested, transformed, and made available for analytics.

Talk about your experience implementing Infrastructure as Code (IaC) solutions with tools like Terraform. Provide examples of how you structured your configurations, the benefits you realized through automation, and how it streamlined your deployment process.

Emphasize the importance of effective communication in your role, especially when collaborating with cross-functional teams. Discuss your experience in conveying technical concepts to non-technical stakeholders or working with business analysts to translate requirements into actionable tasks.

In your response, share your understanding of data security best practices, such as data encryption, access controls, and compliance issues regarding personal data. You could mention specific experiences where you prioritized data security in a cloud environment.

Discuss your strategies for keeping your skills relevant, such as attending industry conferences, participating in online courses, or following reputable blogs and communities. Mention any learning you have done regarding emerging technologies and how you’ve applied new knowledge in practical scenarios.