Technical Skills and Tools Questions

A concise but comprehensive presentation of a candidate's core technical competencies, tool familiarity, and practical proficiency. Topics to cover include programming languages and skill levels, frameworks and libraries, development tools and debuggers, relational and non relational databases, cloud platforms, containerization and orchestration, continuous integration and continuous deployment practices, business intelligence and analytics tools, data analysis libraries and machine learning toolkits, embedded systems and microcontroller experience, and any domain specific tooling. Candidates should communicate both breadth and depth: identify primary strengths, describe representative tasks they can perform independently, and call out areas of emerging competence. Provide brief concrete examples of projects or analyses where specific tools and technologies were applied and quantify outcomes or impact when possible, while avoiding long project storytelling. Prepare a two to three minute verbal summary that links skills and tools to concrete outcomes, and be ready for follow up probes about technical decisions, trade offs, and how tools were used to deliver results.

HardTechnical

0 practiced

Your dashboards query terabytes per day in BigQuery and costs have surged. Provide a prioritized list of cost-optimization strategies (partitioning, clustering, materialized views, BI Engine, query cache, denormalization) and explain trade-offs for accuracy, freshness, and developer effort for each.

MediumTechnical

0 practiced

Explain how you would use Docker to deploy an open-source BI tool (e.g., Superset or Metabase) in production. Cover containerization best practices, secret management for DB credentials, connection pooling, backup strategies, and how to handle persistent metadata/state.

EasyTechnical

0 practiced

From a practical BI analyst perspective, compare Tableau, Power BI, and Looker. For each tool list: 2 primary strengths, 1 typical deployment/governance model, 1 limitation, and give a recommendation for a mid-sized SaaS company that needs embedded analytics + self-service. Keep answers actionable and specific.

HardSystem Design

0 practiced

Design a BI reporting system that satisfies GDPR and SOC2 requirements. Cover data minimization, encryption (at rest/in transit), access controls and RBAC, audit logging, procedures for data subject requests (erasure/export), and periodic compliance reporting. Provide concrete implementation choices (tools or cloud features) where appropriate.

EasyTechnical

0 practiced

Write a single SQL query (Postgres-compatible) to compute total order amount per customer, including customers with zero orders. Schemas:

customers (customer_id uuid PRIMARY KEY, name text)orders (order_id uuid PRIMARY KEY, customer_id uuid REFERENCES customers, amount numeric, created_at timestamp)

Return columns: customer_id, name, total_amount (0.00 when no orders). Also briefly describe indexing or optimization steps you would take to make this query performant on a dataset with ~100M orders.

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