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Data Engineer (Global)

Dandy is transforming the massive ($200B) but antiquated dental industry. Backed by some of the world's leading venture capital investors, we are on an ambitious mission to integrate and simplify every function of the dental practice through technology. By building the operating system for every dental office in America, Dandy is empowering dentists with technology, innovation, and world-class support to achieve more for their practice, their people, and their patients.

Revolutionizing the dental industry is hard…and we need help.

This is an exciting opportunity to shape the future of Dandy’s data engineering and contribute to the development of a mature, high-performing data team. You’ll work across multiple domains, from product analytics to supply chain optimization, ensuring our data systems are scalable, reliable, and production-ready.

If you have a passion for building robust data systems and leading the way toward a more sophisticated data engineering process, we want you to join us.

What You’ll Do:

  • Lead Data Infrastructure Development: Design, build, and maintain scalable data pipelines and ETL processes that power cross-functional teams such as product, operations, and logistics. Help lay the foundation for our data infrastructure as we evolve into a mature, high-performing engineering team.

  • Contribute to the Data Platform: Play a key role in building and enhancing Dandy's data platform—the foundation upon which the entire organization can scale its data-driven decision-making. You'll ensure that the platform is robust, scalable, and integrates seamlessly with data sources, tools, and stakeholders across the business.

  • Take Ownership of Data Pipelines: Own the entire lifecycle of data pipelines—from data collection and transformation to storage and delivery. Focus on building production-ready, efficient, and resilient data systems.

  • Shape Engineering Best Practices: Drive the adoption of best practices for data engineering, documentation, pipeline optimization, and testing. Establish and maintain strong coding standards, data quality processes, and CI/CD practices to ensure data pipelines run smoothly at scale.

  • Collaborate Across Teams: Work closely with data analysts, product managers, and other internal stakeholders to understand their data needs and deliver accurate, reliable solutions that drive actionable insights and decisions.

  • Optimize and Maintain Workflows: Beyond building basic pipelines, you will focus on productionizing data workflows, ensuring they are optimized for reliability, efficiency, and scalability. Develop monitoring and alerting systems to proactively address potential issues.

  • Documentation & Knowledge Sharing: Create and maintain clear, detailed documentation for data architecture, pipeline workflows, and team processes. Help foster a culture of knowledge-sharing and self-sufficiency across the team.

What We’re Looking For:

  • Proven Experience: 4+ years of experience as a Data Engineer, with a strong background in building production-ready data workflows and data pipeline optimization. You have a track record of designing and maintaining scalable, high-performance systems that are reliable and easy to manage in production.

  • Hands-On Technical Expertise: Proficient in Python, Airflow/Dagster, DBT, and cloud platforms like AWS or GCP. You understand how to build and maintain robust ETL processes and data storage solutions that can scale with the business.

  • Production-Ready Data Systems: You have hands-on experience in productionizing data workflows, focusing on performance, monitoring, and resilience. You know how to ensure data pipelines run efficiently and at scale while maintaining high data quality.

  • Collaborative Problem Solver: You excel at working with cross-functional teams, communicating technical concepts to non-technical stakeholders, and aligning team efforts to meet business goals. You’re driven by the challenge of solving complex problems and building effective solutions.

  • Growth-Oriented: You thrive in a high-growth, evolving environment and are eager to take on new challenges. You’re committed to continuous learning and actively seek opportunities to expand your technical and leadership skills.

  • Timezone Flexibility: You are based in a time zone within 3 hours of New York to ensure seamless collaboration with the rest of the team.

Bonus Points:

  • Strong Documentation Skills: You have experience writing clear, comprehensive documentation for data pipelines, architectures, and workflows, helping teams understand and effectively use the systems you build.

  • Customer-Centric Mindset: You have a strong sense of empathy for our customers—dentists—and are excited about building data systems that help them solve real-world problems.

  • Startup Experience: Experience working in an early-stage or rapidly growing company, contributing to the creation of scalable data engineering processes in a dynamic environment.

For full time positions, we offer a wide range of best in class, comprehensive and inclusive employee benefits including healthcare, dental, parental planning, mental health benefits, a 401(k) plan, and paid time off.

Dandy is proud to be an equal-opportunity employer. We are committed to building a diverse and inclusive culture that celebrates authenticity to win as one. We do not discriminate on the basis of race, religion, color, national origin, gender, gender identity, sexual orientation, age, marital status, disability, protected veteran status, citizenship or immigration status, or any other legally protected characteristics.

Dandy also fully complies with the Americans with Disabilities Act (ADA). We are dedicated to embracing challenges and creating an accessible, inclusive workplace for all individuals. If you require any accommodations for your interview or have any questions beforehand, rest assured that we will move at Dandy speed and do everything in our power to meet your needs.

Average salary estimate

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What You Should Know About Data Engineer (Global), Dandy

Dandy is looking for a passionate Data Engineer to join our innovative team and help transform the outdated dental industry! At Dandy, we're not just a tech company; we're on a mission to revolutionize dental practices across America by integrating technology into every function of a dental office. This is an exciting opportunity to be at the forefront of data engineering, shaping the future of our high-performing data team. As a Data Engineer, you'll design and maintain scalable data pipelines, ensuring our data systems are production-ready and reliable. You'll have the chance to collaborate across various teams, working closely with data analysts and product managers to meet their data needs. If you love building robust data systems and enjoy a fast-paced environment where you can continuously grow your skills, we want to hear from you! Join us at Dandy and be part of a transformative journey where your contributions will help empower dentists with cutting-edge technology and support, ultimately leading to better outcomes for their patients.

Frequently Asked Questions (FAQs) for Data Engineer (Global) Role at Dandy
What responsibilities does a Data Engineer at Dandy have?

As a Data Engineer at Dandy, you will lead the development of data infrastructure, design and maintain scalable data pipelines for various departments, and ensure our data platform supports data-driven decision-making across the organization. You'll take ownership of data pipelines from collection to delivery, drive engineering best practices, and collaborate with cross-functional teams to provide reliable, actionable data solutions.

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What qualifications are required for the Data Engineer position at Dandy?

To qualify for the Data Engineer position at Dandy, you should have a minimum of 4 years of experience in data engineering, with hands-on expertise in building production-ready data workflows. Proficiency in Python, Airflow, DBT, and cloud platforms like AWS or GCP is essential, along with a collaborative problem-solving mindset and strong communication skills to work effectively with both technical and non-technical stakeholders.

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What is the company culture like for a Data Engineer at Dandy?

The culture at Dandy is dynamic, inclusive, and growth-oriented, perfect for a Data Engineer looking to thrive in a fast-paced environment. We celebrate diversity and innovation, encourage continuous learning, and promote a collaborative atmosphere where your contributions directly impact our mission to revolutionize the dental industry. At Dandy, we value authenticity and strive to create a workplace where everyone can succeed.

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What opportunities for growth exist for Data Engineers at Dandy?

At Dandy, Data Engineers are encouraged to take on new challenges and expand their skills continuously. You will work on diverse projects, shaping data systems that contribute to the dental industry's transformation, while also benefiting from mentorship and access to resources that support your professional development. This role is ideal for those who are eager to make an impact and advance their careers in a rapidly growing company.

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How does Dandy support work-life balance for Data Engineers?

Dandy understands the importance of work-life balance, especially for Data Engineers who often face complex challenges. We offer flexible working hours to accommodate different time zones and ensure seamless collaboration. Our comprehensive benefits package, including mental health support and paid time off, further promotes a healthy work-life balance, enabling you to perform at your best while enjoying life outside of work.

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Common Interview Questions for Data Engineer (Global)
What are the key components of a robust data pipeline?

When answering this question, focus on discussing the importance of data collection methods, transformation processes, storage solutions, and delivery mechanisms. Highlight the significance of scalability, reliability, and data quality, explaining how each component contributes to an effective data pipeline.

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How do you ensure data quality in your engineering processes?

A solid response would include mentioning practices such as implementing data validation checks during ETL processes, using tools for monitoring data quality, and employing techniques for data cleansing and transformation. You can also mention your commitment to establishing strong coding standards and documentation to enhance overall data integrity.

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Can you explain your experience with ETL processes?

Share specific examples of your ETL experience, including the tools you've used (like Airflow or DBT), the complexity of the data workflows you've managed, and how you approached productionizing these processes to focus on performance, resilience, and monitoring.

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How do you approach collaboration with cross-functional teams?

Discuss your strategy for effective communication with both technical and non-technical team members, such as actively listening to their needs, translating technical concepts into accessible language, and ensuring alignment on business goals. Providing examples of successful collaborations can strengthen your answer.

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What strategies do you employ to optimize data workflows?

Talk about specific techniques you've used to enhance the efficiency of data workflows, such as methodically analyzing existing pipelines, implementing caching or indexing, and automating processes. Emphasize your ability to monitor performance metrics and iteratively improve systems.

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Describe your experience with cloud platforms such as AWS or GCP.

Share details about your hands-on experience with cloud services—mention which specific services you’ve utilized (like S3 for storage or Redshift for data warehousing), how you leveraged these platforms in your previous roles, and any specific challenges you overcame while working in a cloud environment.

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How do you prioritize tasks when managing multiple data projects?

You can discuss methods like using project management tools, assessing impact and urgency, and collaborating with stakeholders to determine priorities. Supporting your answer with examples of how you've effectively handled multiple priorities will illustrate your capabilities.

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What kind of documentation practices do you follow?

In your response, outline the importance of creating clear, comprehensive documentation for data architectures and pipeline workflows. Discuss the tools you utilize for documentation and your strategies for ensuring that documentation remains up-to-date and useful for team members.

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How do you stay current with data engineering trends and technologies?

Talk about the resources you rely on, such as industry blogs, online courses, webinars, and community forums. Emphasize any active participation in data engineering groups or conferences, as well as your approach to applying new knowledge in your projects at Dandy.

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What motivates you to work in data engineering?

Share your passion for solving complex problems, your desire to contribute to technological advancements, and how working at Dandy aligns with these motivations. Discuss the positive impact that well-structured data has on decision-making and how it excites you to help dental practices thrive through technology.

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DATE POSTED
January 5, 2025

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