Technology Stack Knowledge Questions

Assess a candidate's practical and conceptual understanding of technology stacks, including major programming languages, application frameworks, databases, infrastructure, and supporting tools. Candidates should be able to explain common use cases and trade offs for languages such as Python, Java, Go, Rust, C plus plus, and JavaScript, including differences between compiled and interpreted languages, static and dynamic type systems, and performance characteristics. They should discuss application frameworks and libraries for frontend and backend development, common web stacks, service architectures such as monoliths and microservices, and application programming interfaces. Evaluate understanding of data storage options and trade offs between relational and non relational databases and the role of structured query language. Candidates should be familiar with cloud platforms such as Amazon Web Services, Google Cloud Platform, and Microsoft Azure, infrastructure components including containerization and orchestration tools such as Docker and Kubernetes, and development workflows including version control, continuous integration and continuous delivery pipelines, testing frameworks, automation, and infrastructure as code. Assess operational concerns such as logging, monitoring and observability, deployment strategies, scalability, reliability, fault tolerance, security considerations, and common failure modes and mitigations. Interviewers may probe both awareness of specific tools and the candidate's depth of hands on experience, ability to justify technology choices by evaluating trade offs, constraints, and risk, and willingness and ability to learn and evaluate new technologies rather than claiming mastery of everything.

MediumSystem Design

0 practiced

Design a CDC (Change Data Capture) pipeline to capture row-level changes from a MySQL OLTP source and stream them into an analytics store such as Redshift or Snowflake. Include components (Debezium, Kafka, Kafka Connect), serialization format, schema evolution approach, initial snapshot/backfill strategy, ordering guarantees, handling deletes/tombstones, and how to reprocess historical data safely.

HardTechnical

0 practiced

Describe how you would secure a Kafka-based streaming platform to meet SOC2 or similar compliance requirements. Cover encryption in transit and at rest, authentication mechanisms (SASL, mTLS), authorization (ACLs, RBAC), audit logging, key rotation, network segmentation, and operational processes for security patches and incident response.

EasyTechnical

0 practiced

What is a schema registry in a streaming architecture (for example Confluent Schema Registry used with Avro or Protobuf)? Explain how it helps with schema evolution, compatibility modes (backward/forward/none), serialization, and producer/consumer interoperability. Describe operational practices to enforce and test schema compatibility.

HardTechnical

0 practiced

Create a disaster recovery plan for a critical data lake and supporting infra across multiple AWS regions. Include RTO and RPO targets, cross-region S3 replication, database cross-region replication (where possible), orchestration of failover, verification procedures, secrets and IAM considerations during failover, and how to run and validate DR drills regularly.

MediumBehavioral

0 practiced

Tell me about a time when you convinced stakeholders to adopt a new tool or framework (for example dbt, Airflow, or Terraform) for a data engineering team. Describe the business need, how you evaluated options, the pilot you ran, success criteria and metrics you tracked, how you handled training, resistance, and migration, and what the final outcome was.

Unlock Full Question Bank

Get access to hundreds of Technology Stack Knowledge interview questions and detailed answers.

Join thousands of developers preparing for their dream job.