Preparation for the Data Engineer interview should be methodical. Do not focus solely on memorizing syntax; focus on your ability to articulate your thought process. We want to see how you solve problems, not just that you know the answer.

Role-related Knowledge – We evaluate your proficiency in SQL, Python, and cloud-native data tools. You should be prepared to discuss the "why" behind your tool selection, not just the "how."

Problem-solving Ability – We look for candidates who can break down ambiguous, large-scale problems into manageable components. Show us how you iterate toward a solution when faced with incomplete information.

Culture Alignment – At Speechify, we value ownership and direct communication. Be ready to discuss your past projects with honesty, acknowledging both your successes and the lessons learned from failures.

The Speechify interview process is designed to be transparent, efficient, and respectful of your time. From the initial outreach to the final decision, we aim to provide clear instructions so you can focus on performing your best. You can expect a process that emphasizes technical capability early on, followed by deeper engagement with leadership to ensure cultural and strategic alignment.

This timeline provides a high-level view of your journey from initial assessment to final offer. Use this to pace your preparation, ensuring you have allocated enough time for both technical coding practice and deep-dives into our product mission.

Technical Coding

This area tests your fundamental engineering skills. You will likely participate in an online coding assessment where you must solve problems in a live IDE.

• Coding Efficiency – Writing code that is not only correct but performant.
• Problem Decomposition – Breaking down complex requirements into testable units.
• Tooling – Proficiency in standard IDEs and version control.

System Architecture

We need to know you can build systems that grow with our user base.

• Scalability – Designing for future growth.
• Reliability – Strategies for monitoring and alerting.
• Data Integrity – Ensuring accuracy in high-throughput environments.

Behavioral & Strategic Thinking

We want to know how you work within a team and how you approach long-term goals.

• Communication – Can you explain technical risks to the CEO?
• Adaptability – How do you handle pivot points in product strategy?
• Ownership – Taking responsibility for the end-to-end lifecycle of your code.

As a Data Engineer, you will spend your time building and maintaining the infrastructure that supports our product. You will be expected to:

• Build and optimize ETL/ELT pipelines to support data-driven decision-making.
• Collaborate with the CEO and other leadership to define data requirements that align with business goals.
• Monitor data health and performance, proactively identifying and fixing bottlenecks.
• Champion best practices in data engineering across the organization, ensuring we maintain high standards of code quality.

We seek engineers who possess a blend of deep technical skill and a passion for our mission.

• Must-have skills: Proficiency in Python and SQL, experience with large-scale data processing frameworks, and a solid understanding of cloud infrastructure (e.g., AWS, GCP).
• Nice-to-have skills: Experience with real-time streaming platforms (e.g., Kafka) and exposure to machine learning workflows.
• Experience: Proven track record of managing data infrastructure in a high-growth environment.

Q: How difficult is the technical assessment? A: Candidates often describe it as challenging but fair. It focuses on practical application, so ensure your coding fundamentals are sharp.

Q: What is the interview format for the technical portion? A: It is typically an online assessment where you will solve problems in a live IDE with your camera on.

Q: How long does the process take? A: While it varies, the process is designed to be streamlined. Most candidates move through the stages within a few weeks.

Q: What is the most important trait to show? A: We look for a combination of technical competence and a proactive, ownership-oriented mindset.

• Prepare for the Camera: Since your coding assessment is monitored, practice coding while speaking your thoughts aloud to get comfortable with the format.
• Know the Product: Spend time using Speechify; understanding the user experience makes your technical contributions more meaningful.
• Clarify the Requirements: Before diving into a coding problem, ask clarifying questions to ensure you fully understand the constraints.

The role of Data Engineer at Speechify is a unique opportunity to apply your technical expertise to a product that changes lives. We value engineers who are as passionate about the quality of their data as they are about the accessibility of our tools.

Your preparation should focus on balancing your technical coding speed with your ability to design systems that scale. We encourage you to reflect on your past projects and be ready to share the "why" behind your technical decisions. You have the skills to succeed, and with focused preparation, you will be well-positioned to join our team.

This data provides a benchmark for compensation in the industry. Use it to understand the market value of your skillset and to inform your expectations as you progress through the offer stage.