Techstar Group, established in 2002, provides high-quality services in application development, business intelligence, and data warehousing to a global clientele, including major companies like Verizon, Microsoft, and JPMorgan. They specialize in delivering tailored IT solutions through a collaborative approach, leveraging a robust team of experienced engineers, architects, and software developers.

The Data Engineer position at Techstar Group involves developing electric vehicle user models, conducting descriptive analytics, and presenting research findings. Ideal candidates will have a graduate degree in a related field, 2-3 years of experience in data analysis and machine learning, proficiency in Python or MatLab, experience with big data environments, and strong communication and teamwork skills. This role offers a chance to contribute to innovative projects and make significant data-driven decisions.

Explore this guide on Interview Query to understand the interview process and commonly asked questions for the Data Engineer position at Techstar Group.

Submitting Your Application

The initial step is to submit a compelling application that showcases your technical skills and interest in joining Techstar Group as a Data Engineer. Whether you were contacted by a Techstar recruiter or have approached the company yourself, meticulously review the job description and tailor your resume according to the prerequisites.

This may include identifying specific keywords that the hiring managers might use to filter resumes and crafting a targeted cover letter. Ensure you highlight relevant skills and mention your work experiences prominently.

Recruiter/Hiring Manager Call Screening

If your resume is shortlisted, a recruiter from Techstar Group's Talent Acquisition Team will reach out to verify key details like your experience and skill level. Behavioral questions may also be part of the screening process.

Sometimes, the hiring manager might be present during this call to answer your questions about the role and the company. They may also engage in surface-level technical and behavioral discussions.

This initial conversation typically lasts around 30 minutes.

Technical Virtual Interview

Successfully navigating the recruiter round will earn you an invitation for the technical screening round. This round is usually conducted virtually and may include a combination of video conference and screen sharing. Technical questions during this 1-hour interview may focus on Techstar's data systems, ETL pipelines, and SQL queries.

For data engineering roles, take-home assignments regarding product metrics, analytics, and data visualization could be incorporated. You may also be evaluated on your proficiency in machine learning frameworks, statistical modeling, and the use of Python or MATLAB.

Real-scenario problems like case studies may be assigned, depending on the position's seniority.

Onsite Interview Rounds

Following a second recruiter call outlining the next steps, you'll be invited to attend the onsite interview loop. Multiple interview rounds will be conducted during your day at the Techstar office. Your technical abilities, including programming and data modeling capabilities, will be assessed in detail throughout these interviews.

If you were given take-home exercises, there might be a presentation round during the onsite interview for the Data Engineer role at Techstar Group.

Quick Tips For Techstar Group Data Engineer Interviews

Here are three tips for successfully navigating the Data Engineer interview process at Techstar Group:

• Master Key Technologies: Techstar frequently uses technologies like Big Data, cloud environments (AWS, GCP), and machine learning frameworks. Ensure you are adept with these tools.
• Showcase Project Work: Clearly articulate past projects where you developed or optimized data pipelines, especially those involving large datasets or cloud solutions.
• Demonstrate Analytical Strength: Be prepared to discuss how you approach empirical research, data cleaning, and the practical application of statistical methods.

For more detailed interview guides and to practice with relevant questions, visit Interview Query.

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

• Write a SQL query to select the 2nd highest salary in the engineering department. Write a SQL query to select the 2nd highest salary in the engineering department. If more than one person shares the highest salary, the query should select the next highest salary.

• Write a function to find the maximum number in a list of integers. Given a list of integers, write a function that returns the maximum number in the list. If the list is empty, return None.

• Create a function convert_to_bst to convert a sorted list into a balanced binary tree. Given a sorted list, create a function convert_to_bst that converts the list into a balanced binary tree. The function should return a TreeNode holding the root of the binary tree.

• Write a function to simulate drawing balls from a jar. Write a function to simulate drawing balls from a jar. The colors of the balls are stored in a list named jar, with corresponding counts of the balls stored in the same index in a list called n_balls.

• Develop a function can_shift to determine if one string can be shifted to become another. Given two strings A and B, write a function can_shift to return whether or not A can be shifted some number of places to get B.

• What are the drawbacks of having student test scores organized in the given layouts? Assume you have data on student test scores in two different layouts. Identify the drawbacks of these layouts and suggest formatting changes to make the data more useful for analysis. Additionally, describe common problems seen in "messy" datasets.

• How would you locate a mouse in a 4x4 grid using the fewest scans? You have a 4x4 grid with a mouse trapped in one of the cells. You can scan subsets of cells to know if the mouse is within that subset. Describe a strategy to find the mouse using the fewest number of scans.

• How would you select Dashers for Doordash deliveries in NYC and Charlotte? Doordash is launching delivery services in New York City and Charlotte. Describe the process for selecting Dashers (delivery drivers) and discuss whether the criteria for selection should be the same for both cities.

• What factors could bias Jetco's study on boarding times? Jetco, a new airline, has the fastest average boarding times according to a study. Identify potential factors that could have biased this result and what you would investigate further.

• How would you design an A/B test to evaluate subscription pricing changes for a B2B SAAS company? You work at a B2B SAAS company interested in testing different subscription pricing levels. Describe how you would design a two-week-long A/B test to evaluate a price increase and determine if it is a good business decision.

• How much should a ride-sharing app budget for a $5 coupon initiative? A ride-sharing app has a probability (p) of dispensing a $5 coupon to a rider and services (N) riders. Calculate the total budget needed for the coupon initiative.

• What is the probability of riders getting a coupon? A driver using the app picks up two passengers. Determine:

• The probability of both riders getting the coupon.

• The probability that only one of them will get the coupon.

• What is a confidence interval for a statistic and why is it useful? Explain what a confidence interval is, why it is useful to know, and how to calculate it.

• What is the probability of finding an item on Amazon's website? Amazon has a warehouse system where items are located at different distribution centers. Given the probabilities that item X is available at warehouse A (0.6) or warehouse B (0.8), calculate the probability that item X would be found on Amazon's website.

• Is a coin that lands tails 8 out of 10 times fair? You flip a coin 10 times, and it comes up tails 8 times and heads twice. Determine if this is a fair coin.

• What are time series models and why are they needed? Describe what time series models are and explain why they are necessary when simpler regression models exist.

• How would you justify the complexity of building a neural network model and explain predictions to non-technical stakeholders? Your manager asks you to build a neural network model to solve a business problem. How would you justify the complexity of the model and explain its predictions to non-technical stakeholders?

• How would you evaluate and deploy a decision tree model for predicting loan repayment? You are tasked with building a decision tree model to predict if a borrower will repay a personal loan. How would you evaluate if a decision tree is the correct model? How would you evaluate its performance before and after deployment?

• How does random forest generate the forest, and why use it over logistic regression? Explain how random forest generates its forest. Additionally, why would you choose random forest over other algorithms like logistic regression?

• How would you explain linear regression to a child, a first-year college student, and a seasoned mathematician? Explain the concept of linear regression to three different audiences: a child, a first-year college student, and a seasoned mathematician. Tailor your explanations to each audience's understanding level.

• What are the key differences between classification models and regression models? Describe the main differences between classification models and regression models.

What is the average salary for a Data Engineer at Techstar Group?

Q: What are the key responsibilities for the Data Engineer position at Techstar Group? The Data Engineer will develop electric vehicle user models using telematic data, conduct extensive descriptive analytics, and present findings through presentations, reports, and publications.

Q: What qualifications are required for the Data Engineer role? A graduate degree in Data Analytics, Data Science, Computer Science, or a related field, along with 2-3 years of experience in data analysis, machine learning, and statistical modeling. Proficiency in Python or MatLab and hands-on experience with machine learning frameworks like TensorFlow are essential.

Q: What skills are preferred for this position? Preferred skills include experience with Big Data and cloud environments like AWS, attention to detail, flexibility, creativity, strong communication and teamwork skills, and a passion for empirical research.

Q: What is the duration and location for this role? The position is a 6+ months contract with a high possibility of extension, located in Santa Clara, CA.

Q: What should candidates expect during the interview process? Candidates can expect a technical interview process designed to evaluate their problem-solving abilities, technical skills, and cultural fit with the company. You can practice and prepare for the interview using Interview Query.

Unlock your potential and take your data engineering career to new heights with Techstar Group! As you prepare for the Data Engineer position, remember to leverage the wealth of resources available at Interview Query. For an in-depth understanding of what to expect, visit our main Techstar Group Interview Guide, where we've meticulously compiled numerous interview questions and insights specifically for this role. Additionally, explore our guides tailored to other key positions, such as software engineer and data analyst, to broaden your preparation strategy. At Interview Query, our mission is to arm you with the expertise and confidence needed to excel in your interviews. Check out all our company interview guides for more tips, and feel free to reach out with any questions. Good luck on your journey with Techstar Group!