Steampunk is a forward-thinking company that specializes in data exploitation to support mission and business goals, primarily serving Federal clients in the Homeland, Federal Civilian, Health, and DoD sectors. Our commitment to innovation is demonstrated through our Human-Centered delivery methodology and our role as a Change Agent in Federal contracting.

As a Data Engineer at Steampunk, you will be instrumental in developing enterprise-grade data platforms, services, and pipelines to solve complex data problems. We seek individuals with strong technical skills, especially in Python and AWS, excellent communication abilities, and a passion for data and problem-solving. Join us and contribute to our Data Exploitation Practice. For more details on the interview process, visit Interview Query.

Submitting Your Application

The first step is to submit a compelling application that reflects your technical skills and interest in joining Steampunk as a Data Engineer. Whether you were contacted by a Steampunk 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 Steampunk 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 Steampunk data engineer hiring manager stays present during the screening round to answer your queries about the role and the company itself. They may also indulge 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 Steampunk data engineer role usually is conducted through virtual means, including video conference and screen sharing. Questions in this 1-hour long interview stage may revolve around Steampunk’s data systems, ETL pipelines, and SQL queries.

You may be given take-home assignments or live coding tasks that assess your proficiency in Python, AWS, and other necessary tools such as Apache Airflow. Your expertise in manipulating both structured and unstructured data may also be under review.

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 Steampunk office. Your technical prowess, including programming and data architecture 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 Steampunk.

Quick Tips For Steampunk Data Engineer Interviews

You should plan to brush up on any technical skills and try as many practice interview questions and mock interviews as possible. A few tips for acing your Steampunk interview include:

• Understand Agile and DevSecOps: Steampunk looks for individuals who are comfortable working in Agile environments and using DevSecOps practices. Be prepared to discuss your experience and knowledge in these areas.
• Technical Breadth: Given the wide array of technical tools and platforms mentioned, be sure to demonstrate your familiarity with AWS, Python, and big data tools. Refresh your knowledge on data pipeline tools like Airflow and ETL processes.
• Soft Skills Are Key: Excellent communication and customer service skills are crucial. Practice explaining your technical solutions in a clear, non-technical manner to highlight your ability to interface with clients.

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

• How would you explain what a p-value is to someone who is not technical? Explain a p-value as a measure of how likely it is that an observed result occurred by chance. A lower p-value indicates stronger evidence against the null hypothesis.

• Write a function to simulate coin tosses with a given probability of heads. Create a function that takes the number of tosses and the probability of heads as inputs. The function should return a list of 'H' or 'T' representing the outcomes of the coin tosses.

• How much do you expect to pay for a sports game ticket, considering a 20% chance of a scalped ticket not working? Calculate the expected cost by considering the probability of the scalped ticket working and the additional cost if it doesn't. Determine how much money to set aside for the game.

• What is the probability of drawing three cards in increasing order from a shuffled deck of 500 cards? Calculate the probability that each subsequent card drawn from a shuffled deck of 500 cards is larger than the previous one.

• How do you calculate the average lifetime value for a SAAS company with given churn and subscription costs? Determine the formula for average lifetime value using the product cost, monthly churn rate, and average customer duration.

• What metrics would you use to determine the value of each marketing channel? Given all the different marketing channels and their respective costs at Mode, a B2B analytics dashboard company, what metrics would you use to evaluate the value of each marketing channel?

• What would you do if friend requests are down 10% on Facebook? A product manager at Facebook informs you that friend requests have decreased by 10%. What steps would you take to address this issue?

• How would you improve Google Maps and measure the success of your improvements? As the PM on Google Maps, how would you improve the product? What metrics would you use to evaluate the success of your feature improvements?

• How do you calculate the average lifetime value for a SAAS company? For a SAAS company with a product costing $100 per month, a 10% monthly churn rate, and an average customer lifespan of 3.5 months, how would you calculate the average lifetime value?

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

• Write a Python program to check if each string in a list has all the same characters. Given a list of strings, write a Python program to check whether each string has all the same characters or not. Determine the complexity of this program.

• Create a function to determine if a string is a palindrome. Given a string, write a function to determine if it is a palindrome or not. A palindrome reads the same forwards and backwards.

• Write a function to simulate coin tosses based on a given probability of heads. Write a function that takes the number of tosses and the probability of heads as input and returns a list of randomly generated results representing the outcomes of the coin tosses.

• Develop a function to perform bootstrap sampling and calculate a confidence interval. Given an array of numerical values, bootstrap samples, and size for a confidence interval, write a function to perform bootstrap sampling and calculate the confidence interval.

• Write a program to determine the term frequency (TF) values for each term in a document. Given a text document in the form of a string, write a program in Python to determine the term frequency (TF) values for each term in the document. Round the term frequency to 2 decimal points.

• What metrics would you use to track accuracy and validity of a spam classifier model? Assume you have built a V1 of a spam classifier for emails. What metrics would you use to track the model's accuracy and validity?

• How would you evaluate the suitability and performance of 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?

• What is Linear Discriminant Analysis (LDA) and its use cases in machine learning? Explain the concept of Linear Discriminant Analysis (LDA) in machine learning. What are some practical use cases for LDA?

• How would you collect and aggregate unstructured video data for an ETL pipeline? You are designing an ETL pipeline for a model that uses videos as input. How would you collect and aggregate multimedia information, specifically unstructured data from videos?

• How would you determine which search engine performs better and which metrics to track? You are working on building a better search engine for Google. After building it, how would you determine if it serves better results than the existing one in production? Which metrics would you track?

What is the average salary for a Data Engineer at Steampunk.Com?

Q: What skills and qualifications are necessary for the Data Engineer position at Steampunk? To be considered for the Data Engineer role at Steampunk, you should have: - A Bachelor's degree in Computer Science or a related field, or equivalent experience. - 5+ years of direct experience in Data Engineering. - Proficiency with Big Data tools like Hadoop, Spark, and Kafka. - Experience with relational and NoSQL databases, such as Postgres and Cassandra. - Familiarity with ETL tools like Azkaban, Luigi, and Airflow. - Knowledge of AWS cloud services, including EC2, EMR, RDS, and Redshift. - Advanced SQL skills for query authoring and optimization. - Experience with message queuing, stream processing, and working with structured and unstructured data.

Q: What kind of projects will I be working on as a Data Engineer at Steampunk? As a Data Engineer at Steampunk, you will be involved in designing and developing solutions to high-impact, complex data problems. This includes architecting data environments, creating ETL workflows, utilizing visual analytics platforms, and contributing to the growth of our Data Exploitation Practice. You'll also support an Agile software development lifecycle and work closely with data practitioners and other technical teams.

Q: What is Steampunk's company culture like? Steampunk prides itself on being a Change Agent in the Federal contracting industry, with a strong focus on Human-Centered delivery methodology. As an employee-owned company, Steampunk places a high value on investing in its employees, enabling them to do the greatest work of their careers, and rewarding them for their contributions to the company's growth. The company encourages innovation, collaboration, and shared accountability in solving mission challenges.

Q: What benefits can I expect working at Steampunk? The compensation range for the Data Engineer position at Steampunk is between $125,000 to $160,000 annually, depending on various factors like geographic location, experience, and skills. Additionally, Steampunk offers a total compensation package that includes benefits like health insurance, retirement plans, and opportunities for professional development. As an employee-owned company, there are also rewards for outstanding contributions to the company's success.

Q: How can I prepare for the interview process at Steampunk? To effectively prepare for your interview at Steampunk, start by familiarizing yourself with the company's mission, values, and project focus areas. Review the technical skills and tools listed in the job description. Practicing with Interview Query can help you hone your data engineering skills and prepare for potential interview questions. Be ready to discuss your past experiences, problem-solving abilities, and how they align with Steampunk's needs.

To sum up, the Data Engineer role at Steampunk offers an exciting opportunity to work on high-impact, complex data problems alongside some of the best data practitioners in the field. As an industry leader in data exploitation with a focus on Human-Centered Design and DevSecOps, Steampunk provides a dynamic environment that prioritizes innovation and effectiveness. If you're passionate about data and problem-solving, with a robust skill set in tools like Python and AWS, this role could be your next career milestone.

If you want more insights about the company, check out our main Steampunk Interview Guide, where we have covered many interview questions that could be asked. At Interview Query, we empower you to unlock your interview prowess with a comprehensive toolkit, equipping you with the knowledge, confidence, and strategic guidance to conquer every Steampunk interview challenge.

You can check out all our company interview guides for better preparation, and if you have any questions, don’t hesitate to reach out to us.

Good luck with your interview!