Company Technical Strategy Questions

Assessment of a candidate's understanding of the organization's technical direction and how engineering aligns with overall business strategy. This includes knowledge of the technology roadmap, cloud and infrastructure strategy, modernization plans, platform and product priorities, competitive and market positioning, and the team level investments that matter for the near term and long term such as two to three year horizons. Candidates may be evaluated on their ability to analyze tradeoffs between technical options, prioritize engineering work to match business goals, identify risks and technical debt, recommend pragmatic migration or modernization approaches, and communicate how technical choices enable product and market objectives. The topic also covers understanding organizational context including where the team sits in the company, stakeholders and dependencies, and implications for hiring, tooling, and operational practices.

EasyTechnical

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Describe why observability and monitoring are integral to a technical strategy for data platforms. Give three categories of telemetry you would collect (examples: pipeline health, data quality, performance), example tools for each, and how you'd use alerts and dashboards to support SLAs and SLOs.

MediumTechnical

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Your company faces a 20% engineering budget cut. Propose how you'd reprioritize data engineering work to protect critical product functionality and compliance obligations. Include criteria for deferring work, types of projects to keep, and a clear communication plan to stakeholders and executives.

MediumSystem Design

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Design a migration plan to move current on-prem Hadoop-based ETL to AWS S3 + EMR/EKS for 5 PB of data with 1 PB/year growth and a tolerance for up to 48 hours of migration-related lag. Outline phases (discovery, pilot, bulk transfer, live-sync, cutover), required tooling for transfer and validation, data validation strategies, cutover plan, rollback approach, and estimated timeline.

MediumTechnical

0 practiced

Estimate ROI and produce a cost-benefit outline for moving nightly ETL jobs to serverless (e.g., AWS Glue/Dataproc serverless) versus managed Spark clusters. Consider operational cost, developer velocity, scaling needs, cold-start implications, and forecasted data growth over 3 years. State assumptions and sensitivity factors.

HardTechnical

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Your company is evaluating acquiring a startup with proprietary data-processing technology. As the data engineering lead, propose a technical due-diligence checklist covering scalability (benchmarks), security, data lineage, IP and licensing of datasets/code, operational maturity (runbooks, backups), test coverage, portability/lock-in, and integration effort. Prioritize the checklist items and list top red flags that would cause you to recommend walking away.

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