At 10x Genomics, accelerating our understanding of biology is more than a mission—it’s a commitment to revolutionizing the field through innovative research. Our tools have driven groundbreaking discoveries across biology, including cancer, immunology, and neuroscience, by enabling scientists to ask new and profound scientific questions.

In the Data Engineer role, you will be essential in developing and maintaining efficient data pipelines, optimizing ETL processes, and enhancing data visualization using tools like Snowflake and Tableau. The ideal candidate will have robust experience in data engineering, proficiency in SQL and Python, and a keen eye for detail to ensure data integrity and accessibility for comprehensive analysis.

Prepare for this transformative opportunity by exploring our detailed interview guide on Interview Query. Let's get started!

Submitting Your Application

The first step is to submit a compelling application that reflects your technical skills and interest in joining 10x Genomics as a Data Engineer. Whether you were contacted by a 10x Genomics recruiter or have taken the initiative yourself, carefully review the job description and tailor your CV according to the prerequisites.

Tailoring your CV may include identifying specific keywords that the hiring manager might use to filter resumes and crafting a targeted cover letter. Furthermore, don’t forget to highlight relevant skills and mention your work experiences.

Recruiter/Hiring Manager Call Screening

If your CV happens to be among the shortlisted few, a recruiter from the 10x Genomics Talent Acquisition Team will make contact and verify key details like your experiences and skill level. Behavioral questions may also be a part of the screening process.

In some cases, the hiring manager stays present during the screening round to answer your queries about the role and the company itself. They may also engage in surface-level technical and behavioral discussions.

The whole recruiter call should take about 30 minutes.

Technical Virtual Interview

Successfully navigating the recruiter round will present you with an invitation for the technical screening round. Technical screening for the 10x Genomics Data Engineer role is usually conducted through virtual means, including video conference and screen sharing. Questions in this 1-hour long interview stage may revolve around data systems, ETL pipelines, and SQL queries.

You may also face questions related to trend analysis, yield enhancement methods, correlation and ANOVA analysis, statistical process control, and cloud-based platforms. Apart from these, your proficiency in handling databases, automation processes, and data visualization tools may also be assessed during the round.

Depending on the seniority of the position, case studies and similar real-scenario problems may also be assigned.

Onsite Interview Rounds

Followed by a second recruiter call outlining the next stage, you’ll be invited to attend the onsite interview loop. Multiple interview rounds, varying with the role, will be conducted during your day at the 10x Genomics office. Your technical prowess, including programming, data pipeline development, and statistical analysis capabilities, will be evaluated against the finalized candidates throughout these interviews.

If you were assigned take-home exercises, a presentation round may also await you during the onsite interview for the data engineer role at 10x Genomics.

Quick Tips For 10X Genomics Data Engineer Interviews

• Master the Core Technologies: Familiarize yourself with tools and platforms such as Snowflake, Tableau, and Python. Make sure to understand their applications in data management and visualization in a life sciences context.
• Brush Up on Statistical Methods: Ensure you are comfortable with statistical analysis, including ANOVA and SPC methodologies. These skills are critical for 10x Genomics’ data-driven decision-making processes.
• Prepare for Collaborative Scenarios: Demonstrate your ability to work in multidisciplinary teams involving customer-facing support, finance, logistics, manufacturing engineering, quality, and R&D. Effective communication and collaboration are key attributes highly valued at 10x Genomics.

Sign up on Interview Query

Typically, interviews at 10X Genomics vary by role and team, but commonly Data Engineer interviews follow a fairly standardized process across these question topics.

• Write a function calculate_rmse to calculate the root mean squared error of a regression model. The function should take in two lists, one that represents the predictions y_pred and another with the target values y_true.

• Write a query to get the last transaction for each day from a table of bank transactions. Given a table of bank transactions with columns id, transaction_value, and created_at, write a query to get the last transaction for each day. The output should include the id of the transaction, datetime of the transaction, and the transaction amount. Order the transactions by datetime.

• Write a function random_key that returns a key at random with a probability proportional to the weights. Given a dictionary with weights, write a function random_key that returns a key at random with a probability proportional to the weights.

• Write a function to get a sample from a standard normal distribution. Create a function to generate a sample from a standard normal distribution.

• Write an efficient function nearest_entries to find the closest element to N and its k-next and k-previous elements in a sorted list. Given a sorted list of integers ints with no duplicates, write an efficient function nearest_entries that takes in integers N and k and finds the element closest to N along with the k-next and k-previous elements of the list.

• How would you analyze the churn behavior of users on different Netflix pricing plans? Netflix has two pricing plans: $15/month or $100/year. An executive wants to understand the churn behavior of users on these plans. What metrics, graphs, and models would you use to provide an overarching view of subscription performance?

• How would you predict which merchants DoorDash should acquire in a new market? As a data scientist at DoorDash, you need to build a model to predict which merchants the company should target for acquisition when entering a new market. How would you approach this task?

• How would you value the benefit of keeping a hit TV show on Netflix? Netflix executives are considering renewing a deal with another TV network for exclusive streaming rights to a hit TV series. The show has been on Netflix for a year. How would you approach valuing the benefit of keeping this show on Netflix?

• How would you measure and address the success of LinkedIn’s newsfeed ranking algorithm?

• How would you measure the success of LinkedIn’s newsfeed ranking algorithm?

• If some success metrics for the newsfeed algorithm are improving while others are declining, how would you approach this situation?

• How would you determine the statistical significance of an A/B test for a landing page redesign? You want to launch a redesign of a landing page to improve the click-through rate using an A/B test. How would you infer if the results of the click-through rate were statistically significant?

• How would you explain what a p-value is to someone who is not technical? Explain the concept of a p-value in simple terms to a non-technical person. Focus on its role in hypothesis testing and what it indicates about the results.

• How many more samples would we need to decrease the margin of error from 3 to 0.3? Given a sample size (n) with a margin of error of 3, calculate the additional number of samples required to reduce the margin of error to 0.3.

• How would you determine if the results of an AB test on a landing page redesign are statistically significant? Describe the process of analyzing AB test results to determine if the observed differences in click-through rates are statistically significant.

• How would you build a model to predict which merchants DoorDash should acquire in a new market? As a data scientist at DoorDash, how would you develop a model to identify which merchants the company should target for acquisition when entering a new market?

• How would you assign point values to letters in a Spanish Scrabble game without knowing Spanish? If you need to build a Scrabble game for Spanish users and you don't know Spanish, how would you determine the point values for each letter?

What is the average salary for a Data Engineer at 10X Genomics?

Q: What does a Data Engineer at 10X Genomics do?
A: As a Data Engineer at 10X Genomics, you will develop data pipelines, design analytics tools, and ensure data accessibility. You will be involved in process control, yield optimization, data analysis, and collaborating with stakeholders to optimize ETL processes and data integration.

Q: What skills are required for a Data Engineer position at 10X Genomics?
A: Key skills include proficiency in SQL, Python, and cloud-based data platforms like Snowflake and AWS. Experience in ETL development, statistical analysis software (e.g., JMP, R, Minitab), data visualization tools (e.g., Tableau), and a strong understanding of Operations processes are also critical.

Q: What is the interview process like for the Data Engineer role at 10X Genomics?
A: The interview process typically includes a phone screen with HR, technical interviews assessing coding, data engineering skills, and problem-solving abilities, followed by onsite interviews to evaluate cultural fit and deeper technical aspects.

Q: What is the company culture at 10X Genomics?
A: 10X Genomics has an inclusive and dynamic environment that encourages innovation and collaboration. Employees are empowered to follow their passions and pursue new ideas, working together to drive advancements in the life sciences.

Q: How can I prepare for a Data Engineer interview at 10X Genomics?
A: To prepare, research the company, review your technical skills, and practice common interview questions using Interview Query. Familiarize yourself with the core technologies used at 10X Genomics, such as Snowflake, Tableau, and Python, and be ready to discuss your past experiences and projects.

For those aiming to make a significant impact in the rapidly evolving field of biotechnology, the Data Engineer position at 10x Genomics presents an incredible opportunity. You'll be at the forefront of developing cutting-edge data engineering solutions, collaborating with diverse teams, and driving forward actionable insights that can change the world. Eager to learn more about what it takes to succeed at 10x Genomics? Dive into our comprehensive 10X Genomics Interview Guide, where we cover a variety of interview questions and offer detailed insights into other roles such as Software Engineer and Data Scientist. At Interview Query, we're dedicated to empowering you with the tools, confidence, and strategic guidance you need to master your interviews at 10x Genomics. Check out all our company interview guides for a more in-depth preparation, and feel free to reach out with any questions. Good luck with your interview!