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Suppose there exists a new airline named Jetco that flies domestically across North America. Jetco recently had a study commissioned that tested the boarding time of every airline, and it came out that Jetco had the fastest average boarding times of any airline.

What factors could have biased this result, and what would you look into?

What could potentially bias the average boarding time in favor of an airline that only flies domestically?

What could potentially bias the average boarding time in favor of an airline that only flies domestically?

Boarding Times Bias

A new airline came out as the fastest average boarding times compared to other airlines.  What factors could have biased this result and what would you look into?

Statistics

You are testing hundreds of hypotheses with many t-tests. What considerations should be made?

What is a key disadvantage of the F-test when compared to multiple t-tests?

What is a key disadvantage of the F-test when compared to multiple t-tests?

Hundreds of Hypotheses

You are testing hundreds of hypotheses with many t-tests. What considerations should be made?

Let’s say you work for a social media company that has just done a launch in a new city. Looking at weekly metrics, you see a slow decrease in the average number of comments per user from January to March in this city.

The company has been consistently growing new users in the city from January to March.

What are some reasons why the average number of comments per user would be decreasing and what metrics would you look into?

What metric could be used to measure if active users are still engaging on the platform despite an overall decrease in the average number of comments per user?

What metric could be used to measure if active users are still engaging on the platform despite an overall decrease in the average number of comments per user?

Decreasing Comments

How would you investigate a decline in the average number of comments per user?

Product Metrics

Job Title: GCP Data EngineerExperience: 5 to 9 YearsBudget: 15 to 20 LPALocation: Gurgaon (Hybrid)Relocation works as the interviews will be virtual Skills: GCP, BigQuery, Dataproc, Dataflow, Python, SQL Role OverviewWe are looking for an experienced GCP Data Engineer with strong hands-on expertise in building, managing, and optimizing large-scale data pipelines on Google Cloud Platform. The ideal candidate should have solid experience with BigQuery, Dataproc, Dataflow, and end-to-end data engineering workflows. Key Responsibilities<ul><li>Design, develop, and maintain scalable data pipelines on GCP using BigQuery, Dataproc, Dataflow, Pub/Sub, and Cloud Storage.</li><li>Build and optimize data ingestion, ETL/ELT processes, and distributed data processing workflows.</li><li>Work with large datasets to ensure high performance, reliability, and data quality within data platforms.</li><li>Implement data transformation logic using Python, SQL, PySpark or similar technologies.</li><li>Optimize BigQuery queries, partitioning, clustering, and cost management.</li><li>Collaborate with analytics, BI, and application teams to deliver data solutions aligned with business needs.</li><li>Ensure security, governance, and compliance across the GCP data ecosystem.</li></ul> Required Skills & Experience<ul><li>5–10 years of total experience with minimum 3+ years in GCP data engineering.</li><li>Strong hands-on experience in BigQuery, Dataproc, Dataflow, Cloud Composer/Airflow.</li><li>Strong SQL and Python skills; experience in Spark or PySpark preferred.</li><li>Good understanding of data warehousing concepts, ETL/ELT architectures, and distributed data processing.</li><li>Experience with CI/CD pipelines, Git, and DevOps practices in cloud environments.</li><li>Knowledge of Pub/Sub, Cloud Storage, Cloud Functions will be an added advantage.</li></ul>

Job Title: AWS Data EngineerExperience: 5 to 10 YearsBudget: 25 to 32 LPALocation: BangaloreType: Full-Time Primary Skills: AWS Glue , Lamda , Redshift , Python , Pyspark , Sql We’re looking for an AWS Data Engineer who has strong, hands-on experience with AWS Glue, Lambda, Redshift, Python, PySpark, and SQL. This role will focus on building and maintaining data pipelines in AWS and helping us improve how data flows through our systems. What you’ll be working on<ul><li>Building and maintaining ETL/ELT pipelines using AWS Glue and PySpark.</li><li>Writing Lambda functions in Python for automation and event-driven workflows.</li><li>Working with Redshift for data warehousing, including query optimization and data modeling.</li><li>Writing and tuning SQL for transformations, reporting, and general data processing.</li><li>Setting up and managing data movement across S3, Glue Catalog, Redshift, and other AWS services.</li><li>Troubleshooting issues in data jobs and improving overall performance and reliability.</li><li>Collaborating with analysts, data scientists, and cross-functional teams to support data needs.</li></ul> What we’re looking for<ul><li>Strong hands-on experience with AWS Glue and PySpark.</li><li>Good working knowledge of AWS Lambda and Python-based automation.</li><li>Experience with Redshift (including performance tuning, distribution keys, sort keys, etc.).</li><li>Solid SQL skills and experience working with large datasets.</li><li>Familiarity with data modeling, ETL processes, and general data engineering best practices.</li><li>Ability to work independently and take ownership of end-to-end data workflows.</li><li>Strong problem-solving skills and willingness to dive deep into data issues.</li></ul> Nice to have<ul><li>Experience with AWS Step Functions or other orchestration tools.</li><li>Exposure to CI/CD practices, version control, and basic DevOps workflows.</li><li>Knowledge of data quality frameworks or monitoring tools.</li><li>Experience with Glue Studio, Redshift Spectrum, or Athena.</li></ul>

Job Title: Azure Data EngineerExperience: 5 to 8 YearsBudget: 18 to 20 LPALocation: BangaloreType: Full-Time You will be responsible for Data Integration and Transformation: Implement the ETL/ELTs to move data betweenthe raw, trusted, and curated data layers of data lake supporting various real time andbatch cyber use case.Data Modelling: Implement the logical and physical data model for the cyber dataproducts to support threat detection, incident response and reporting.Coding and Documentations: Contribute to raising the quality bar of the team'scodebase by producing high-quality code and documentation of data pipelines, datamodels and their quality metrics.Collaboration and Communication: Collaborate and communicate effectively withstakeholders and members of the data team and actively participate in monitoring andimproving the data quality of the cyber data products. You will need A strong passion for bigdata, data modelling, data quality and ETLsProficiency in SQL and programming languages like PythonWorking knowledge of ETL and ELT frameworks, data modelling and orchestration toolslike Airflow and dbtExperience working with cloud data platforms e.g. Databricks on AzureGood understanding of data lakes and data warehouses conceptsGood practical understanding of version control systems such as GitExperience working with BI tools like TableauKnowledge of cybersecurity principles and practices

Job Title: Data EngineerExperience: 4 to 8 YearsBudget: 22.5 LPALocation: Mumbai, BangaloreType: Full-Time Job Description: Data Engineer (Python, PySpark, Spark, SQL, AWS/Azure)We’re looking for a Data Engineer who has solid, hands-on experience working with Python, PySpark, Spark, SQL, and either AWS or Azure. This role is focused on building and maintaining reliable data pipelines and helping us improve how we store, process, and use data across the company. What you’ll do<ul><li>Build and maintain data pipelines using Python and PySpark.</li><li>Work with Spark to process large datasets and improve performance where needed.</li><li>Write and tune SQL for data extraction, transformation, and reporting.</li><li>Work with our cloud environment (AWS or Azure) to move and manage data.</li><li>Collaborate with data analysts, data scientists, and engineering teams to support their data needs.</li><li>Help improve data quality, monitoring, and overall reliability of our data systems.</li><li>Troubleshoot issues in data workflows and optimize jobs for better speed and stability.</li></ul> What we’re looking for<ul><li>Strong, practical experience with Python and PySpark.</li><li>Experience with Databricks.</li><li>Very comfortable working with Spark in a production environment.</li><li>Solid SQL skills — you should be able to write and optimize complex queries.</li><li>Hands-on experience with AWS or Azure data services.</li><li>Understanding of data modeling, ETL/ELT processes, and general data engineering best practices.</li><li>Ability to work independently and take ownership of projects.</li><li>Someone who enjoys solving problems and digging into messy datasets.</li></ul> Nice to have<ul><li>Familiarity with Airflow, Data Factory, Glue, or other orchestration tools.</li><li>Some exposure to CI/CD, Git, or general DevOps workflows.</li><li>Knowledge of data governance or security practices.</li></ul>

Job Title: Data Engineer Experience: 5 to 7 YearsBudget: 17 to 25 LPALocation: BangaloreType: Full-Time <ul><li>Design and Development:</li><li>Design, develop, and maintain scalable and robust data pipelines (ETL/ELT) using PySpark on the Databricks platform.</li><li>Implement data ingestion strategies to load data from various sources (e.g., streaming, APIs, databases, files) into the Data Lake/Data Warehouse.</li><li>Write optimized and complex SQL queries for data extraction, transformation, and loading.</li><li>Platform & Optimization:</li><li>Leverage expertise in a Cloud Platform (AWS/Azure/GCP) for cloud-native data services, storage solutions (e.g., S3, ADLS, GCS), and compute resources.</li><li>Optimize and fine-tune Spark jobs and Databricks clusters for performance, cost efficiency, and reliability.</li><li>Ensure data quality, integrity, and security across all data lifecycle stages.</li><li>Collaboration & Operations:</li><li>Collaborate with Data Scientists, Analysts, and other engineering teams to understand data requirements and deliver solutions that meet business needs.</li><li>Implement and maintain CI/CD pipelines and version control (e.g., Git) for data pipeline deployments.</li><li>Monitor and troubleshoot production data pipelines and proactively address issues.</li></ul>

Job Title: Data EngineerExperience: 6 to 10 YearsBudget: 20 to 30 LPALocation: BangaloreType: Full-Time We are hiring sharp, hands-on Data Engineers to build scalable data solutions and drive performance across both traditional and cloud-based data platforms. Key Roles and Responsibilities.<ul><li>5+ years of hands-on experience in Data Engineering</li><li>Strong command over SQL, Python, and PySpark for data manipulation and analysis</li><li>Deep experience with data warehousing concepts and implementation in cloud environments (Azure/AWS)</li><li>Proficiency in data modeling techniques for cloud-based systems</li><li>(Databricks, Snowflake)</li><li>Solid understanding of ETL/ELT processes and best practices in cloud architectures</li><li>Experience with dimensional modeling, star schemas, and data mart design</li><li>Strong analytical thinking and problem-solving skills</li></ul>

Question	Topic	Difficulty	Ask Chance
Boarding Times Bias	Statistics	Medium	Very High
Hundreds of Hypotheses	Statistics	Medium	Very High
Decreasing Comments	Product Metrics	Easy	Very High

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