The Shifting Landscape of Tech Hiring
The technology industry has undergone a dramatic transformation over the past two years. What was once an employee's market, where software engineers could command multiple offers from top companies, has become a far more competitive environment. The numbers tell a sobering story: Meta laid off over 21,000 employees across 2022 and 2023. Amazon cut approximately 27,000 positions. Google eliminated 12,000 roles. Salesforce reduced its workforce by 10%. These are not isolated incidents but part of a broader pattern affecting virtually every major technology company.
For data professionals, this shift has created both challenges and opportunities. While positions at FAANG companies (Facebook, Amazon, Apple, Netflix, Google) have become increasingly scarce, thousands of mid-size companies, startups, and enterprises outside the traditional tech sector are actively hiring data analysts, data engineers, and SQL developers. These companies range from financial technology startups to healthcare organizations, from e-commerce platforms to manufacturing firms embracing digital transformation.
The critical question for job seekers becomes: how do you prepare for interviews at companies that operate very differently from the tech giants?
The Problem with Generic SQL Interview Prep
Walk into any online learning platform or interview preparation resource, and you will find an abundance of SQL practice questions. The majority of these questions follow familiar patterns: find the top 10 customers by purchase amount, calculate monthly active users, determine which products have the highest revenue. While these problems teach fundamental SQL concepts, they share a common limitation.
These generic questions are often modeled after the types of problems encountered at large technology companies. They assume you are working with user engagement data, e-commerce transactions, or social media metrics. The tables are clean. The relationships are straightforward. The business context is vague enough to apply anywhere.
This approach creates a significant gap when you interview at companies outside the traditional tech sector. A fintech company does not care whether you can calculate monthly active users. They want to know if you can identify potentially fraudulent transactions. A healthcare organization is not interested in your ability to rank products by revenue. They need someone who understands how to query patient data while respecting the complexities of medical records and regulatory requirements.
Understanding Domain-Specific SQL Challenges
Every industry has its own data patterns, terminology, and analytical priorities. When you walk into an interview at a specialized company, the questions you face will reflect the actual problems their data teams solve daily.
In financial services, a candidate might be asked to detect suspicious transaction patterns by analyzing spending behavior across time zones and merchant categories. The interviewer is not just testing your ability to write a window function. They want to see if you understand what makes a transaction look fraudulent and how to translate that intuition into a query.
Healthcare interviews often involve patient cohort analysis, where you must identify groups of patients who share certain characteristics across multiple clinical systems. The challenge goes beyond writing correct SQL. You need to demonstrate awareness of how medical data is structured and why certain relationships between diagnoses, treatments, and outcomes matter.
E-commerce companies with sophisticated analytics needs might ask you to calculate customer lifetime value using cohort analysis, or to identify products at risk of stockout based on sales velocity and supplier lead times. These queries combine multiple metrics in ways that require genuine understanding of retail operations.
Real estate and property technology firms generate complex datasets combining property characteristics, market conditions, and geographic factors. An interview question might ask you to find comparable properties for valuation, adjusting for differences in features and locations. This requires both technical skill and domain awareness.
For detailed breakdowns of SQL challenges specific to each industry, see our deep-dive articles on SQL in Finance and Fintech, SQL in Healthcare, and SQL in E-commerce and Retail.
Why Domain Knowledge Matters in Interviews
When an interviewer at a healthcare company asks you to find all patients who had a particular diagnosis code within 30 days of a hospital admission, they are evaluating more than your ability to write a date filter. They are assessing whether you understand how healthcare data is structured and whether you can translate a clinical question into a technical query.
This domain awareness signals several important qualities to potential employers. First, it demonstrates that you can communicate effectively with non-technical stakeholders. Business users do not think in terms of JOIN operations and GROUP BY clauses. They think about patients, transactions, policies, and outcomes. A candidate who understands the domain can bridge this gap.
Second, domain knowledge reduces the ramp-up time for new hires. Every company has unique data systems and business processes, but candidates who already understand the industry's common patterns can become productive more quickly. This is particularly valuable for smaller companies that may not have extensive training programs.
Building Domain-Specific SQL Skills
Developing expertise in domain-specific SQL requires a deliberate approach that combines technical practice with industry knowledge. The process begins not with writing queries, but with understanding the business context you are targeting.
Before diving into practice problems, spend time learning the industry. Read publications and analyst reports. Understand the terminology and common metrics. Follow news about major companies in the space to understand current trends and challenges. This foundation makes your technical practice far more effective.
When you do practice, seek out environments that offer realistic schemas and sample data rather than generic tables. SQLSandboxes provides industry-specific case studies that simulate real business scenarios, complete with properly structured schemas and challenges that mirror actual interview questions.
For a comprehensive guide on developing domain expertise alongside technical skills, read our article on Building Domain-Specific SQL Skills: A Complete Guide.
The Competitive Advantage of Specialization
In a job market where thousands of candidates can demonstrate basic SQL proficiency, specialization provides a meaningful competitive advantage. Employers interviewing for data roles at specialized companies often find that many candidates have strong technical foundations but lack the contextual understanding to apply those skills effectively.
By investing in domain-specific preparation, you position yourself differently in the hiring process. You can discuss not just how you would write a query, but why that query matters to the business. You can ask informed questions about the company's data challenges. You can demonstrate that you will contribute value from your first day rather than requiring extensive training to understand the business context.
This advantage becomes particularly significant at mid-size companies and growing startups where every hire must contribute quickly. These companies often cannot afford the extended onboarding periods that larger organizations might provide. They seek candidates who bring both technical skills and relevant domain knowledge.
Getting Started Today
The path from generic SQL practice to domain-specific expertise requires deliberate effort, but the investment pays dividends throughout your career. Start by selecting an industry focus based on your interests and background. Research that industry to understand its data patterns and challenges. Then, practice with realistic scenarios that reflect the actual problems you will encounter in interviews.
SQLSandboxes offers the tools you need to develop domain-specific SQL skills. The Interview Prep feature generates custom practice problems tailored to specific job descriptions and industries. The Case Studies section provides comprehensive scenarios across multiple industries including healthcare, finance, e-commerce, and social media. The SQL Editor lets you practice with domain-specific databases featuring realistic schemas and data.
The job market has changed, and your preparation must change with it. Generic SQL practice remains valuable for building foundational skills, but landing roles at specialized companies requires demonstrating that you understand their specific challenges. By developing domain expertise alongside technical proficiency, you position yourself for success in the competitive job market of 2026 and beyond.