Prepare for and practice interview questions from Apptad Inc..

Apptad Inc. Interview Questions

A/B Testing

Algorithms

Analytics

Machine Learning

Probability

Product Metrics

Python

Statistics

Apptad Inc. Interview Guides

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?

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?

In an A/B test, how can you check if assignment to the various buckets was truly random?

In an A/B test, which of the following is a common method to determine if the assignment to the test groups was truly random?

In an A/B test, which of the following is a common method to determine if the assignment to the test groups was truly random?

Random Bucketing

A/B Testing & Experimentation

Apptad Inc. Salaries by Position

Senior Java Developer – 10+ Years ExperienceWe are seeking a highly skilled and experienced Java Developer with over 10 years of hands-on experience in backend development, cloud technologies, and modern DevOps practices. The ideal candidate will have a strong background in Java and Spring Boot, with proven expertise in AWS cloud services, stream processing, and container orchestration.Key Qualifications:10+ years of professional experience in Java development, with deep expertise in Spring Boot and microservices architecture.3+ years of hands-on experience working in AWS cloud environments, including services such as EC2, S3, Lambda, RDS, etc.Strong experience with stream processing frameworks such as Kafka Streams, and familiarity with Apache Kafka or Confluent Kafka.Solid understanding of PostgreSQL or similar relational databases.Proficient in DevOps practices and tools including Jenkins, Terraform, Nexus, and CI/CD pipelines.Experience with containerization and orchestration tools such as Docker, Kubernetes, AWS EKS, and ECS.Familiarity with messaging systems like Apache Kafka, RabbitMQ, or similar.Exposure to financial domain messaging formats (e.g., XML, JSON, and mainframe message formats) is a strong plus.Preferred Attributes:Strong problem-solving skills and ability to work independently in a fast-paced environment.Excellent communication and collaboration skills.Experience working in Agile/Scrum teams.

Job Title: Azure Data EngineerLocation: Toronto, ON (Hybrid) This role requires deep technical expertise in Azure data services, modern data architecture, and best practices in data engineering, security, and automation. Key Responsibilities:Architecture & Solution Design:<ul><li>Architect cloud-native data solutions using Azure Data Lake, Synapse, Databricks, and Data Factory.</li><li>Define the end-to-end data architecture including ingestion, transformation, modeling, storage, and consumption layers.</li><li>Lead the adoption of Delta Lake, lakehouse patterns, streaming architectures, and medallion models.</li><li>Evaluate new Azure capabilities and make recommendations to improve data strategy and platform maturity.</li></ul> Data Pipeline & Platform Development:<ul><li>Build highly scalable, fault-tolerant ETL/ELT pipelines using ADF, Databricks, Synapse pipelines, and Azure Functions.</li><li>Write complex transformations using PySpark, SQL, Python, and Spark best practices.</li><li>Optimize pipeline performance, cost efficiency, and reliability through tuning and automation.</li></ul> Data Governance, Quality & Security:<ul><li>Establish data quality frameworks, validation rules, observability, and automated testing.</li><li>Implement enterprise-grade security including RBAC, Key Vault integration, encryption, and audit controls.</li><li>Work with governance teams to enable lineage, metadata management, and cataloging with Azure Purview.</li></ul> Leadership & Collaboration:<ul><li>Mentor and guide junior/intermediate data engineers on Azure best practices.</li><li>Partner with architects, data scientists, BI developers, and business teams to deliver high-impact data solutions.</li><li>Lead technical design reviews, code reviews, and cloud architecture discussions.</li></ul> DevOps & Automation:<ul><li>Develop CI/CD pipelines using Azure DevOps or GitHub Actions for automated deployment of data workloads.</li><li>Create and maintain Infrastructure as Code (IaC) using ARM/Bicep or Terraform.</li><li>Implement monitoring and logging using Azure Monitor, Log Analytics, and Databricks monitoring tools.</li></ul> Required Qualifications:<ul><li>7–12+ years of experience in data engineering or software engineering.</li><li>Advanced experience with Azure Data Factory, Azure Databricks, Azure Synapse Analytics, ADLS Gen2.</li><li>Expert proficiency in SQL, PySpark, and Python.</li><li>Strong experience designing large-scale data architectures (lakehouse, data warehouse, streaming).</li><li>Solid understanding of advanced ETL/ELT patterns, orchestration, and distributed computing.</li><li>Proven experience optimizing Spark clusters, query performance, and cloud spend.</li><li>Hands-on experience implementing CI/CD and IaC in Azure environments.</li><li>Strong knowledge of Azure security best practices (managed identities, RBAC, networking, encryption).</li></ul> Preferred Qualifications:<ul><li>Experience building streaming pipelines using Event Hub / Kafka / Spark Structured Streaming.</li><li>Background enabling ML/AI data pipelines or feature stores.</li><li>Familiarity with Power BI, semantic models, and analytics ecosystems.</li><li>Azure certifications: DP-203, DP-500, AZ-305, or similar.</li><li>Experience in regulated industries (finance, insurance, public sector).</li></ul>

Question	Topic	Difficulty	Ask Chance
Boarding Times Bias	Statistics	Medium	Very High
Hundreds of Hypotheses	Statistics	Medium	Very High
Random Bucketing	A/B Testing & Experimentation	Medium	Very High

Apptad Inc. Interview Questions

Apptad Inc. Interview Guides

Apptad Inc. Interview Questions

Apptad Inc. Salaries by Position

Apptad Inc. Opening Jobs