Relevant Technical Experience and Projects Questions

Describe the hands on technical work and projects that directly relate to the role. Cover specific tools and platforms you used, such as forensic analysis tools, operating systems, networking and mobile analysis utilities, analytics and database tools, and embedded systems or microcontroller development work. For each item explain your role, the scope and scale of the work, key technical decisions, measurable outcomes or improvements, and what you learned. Include relevant certifications and training when they reinforced your technical skills. Also discuss any process improvements you drove, cross functional collaboration required, and how the project experience demonstrates readiness for the role.

MediumSystem Design

0 practiced

Design a metadata and lineage solution so analysts can discover datasets and trace transformations from source to BI dashboards. Compare using managed services (Glue/Hive metastore + Amundsen/Atlas) versus building a custom solution. Explain how you'd capture lineage automatically from orchestrators (Airflow/Spark) and visualize it for stakeholders.

MediumTechnical

0 practiced

A Spark job that joins a large 1TB fact table with a 100MB dimension is slow and causes OOMs. Explain step-by-step how you'd diagnose and optimize this job: discuss partitioning strategy, broadcast joins, reducing shuffle, memory tuning, data serialization, and possible preprocessing to reduce input size.

MediumTechnical

0 practiced

Walk through implementing a CDC pipeline from MySQL to a data lake using Debezium and Kafka Connect: explain snapshot vs incremental strategies, connector configuration, handling schema changes, ensuring idempotent or exactly-once delivery into the sink, and monitoring/alerting for lag or connector failures.

MediumSystem Design

0 practiced

Design an Airflow-based orchestration for daily ETL pipelines that must support backfills, incremental runs, SLA guarantees, and graceful handling of downstream consumers. Describe DAG structure, sensor choices, retry and parallelism settings, handling of backfill windows, and strategies to prevent cascading failures during backfills.

MediumTechnical

0 practiced

Explain how you implemented data-quality checks for a batch processing pipeline: which framework you used (Great Expectations, Deequ, custom), where checks run (pre/post-load), how failures are surfaced and triaged, and how you maintained trust in the checks while avoiding false positives.

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