Data Analyst (SQL)

TL;DR

Data Analyst (SQL): Supporting internal teams with one-off data reports, SQL query writing, and query review with an accent on data accuracy, performance optimization, and business logic validation. Focus on translating complex business requirements into reliable data outputs and ensuring the integrity of reporting across product, finance, and CRM systems.

Salary: €45,000 – €70,000 gross per year

Company

hirify.global is a company focused on internal data management and reporting across various business platforms.

What you will do

• Create one-off reports using SQL based on business and operational requests.
• Translate reporting needs from management, product, finance, CRM, and operations into accurate data outputs.
• Write, review, and improve SQL queries used in reports, dashboards, and internal tools.
• Analyze existing queries to identify issues such as incorrect joins, duplicate counting, or inefficient logic.
• Review slow or heavy queries and suggest improvements to performance and structure.
• Validate that reported numbers are accurate and aligned with business definitions.

Requirements

• Strong SQL experience in production environments.
• Ability to write, review, and optimize complex SQL queries.
• Good understanding of joins, aggregations, subqueries, CTEs, indexes, and query execution logic.
• Experience working with relational databases such as MySQL or PostgreSQL.
• Ability to understand business requirements and convert them into reliable data outputs.
• Strong attention to detail and ability to identify inconsistencies in data.

Nice to have

• Experience with BI or reporting tools such as Metabase, Power BI, Tableau, or Looker.
• Experience working with Laravel/PHP-based applications or product databases.
• Experience with finance, CRM, payments, user activity, or high-volume transactional data.
• Understanding of database performance analysis and execution plans.

Culture & Benefits

• Opportunity to work with real business data and influence reporting structures.
• Focus on ownership and accountability for data quality.
• Collaborative environment working closely with technical, product, and management stakeholders.