SQL Engineer

Job Summary

We are seeking a highly analytical and business-savvy SQL Engineer with a strong retail background and expertise in financial metrics, particularly Profit & Loss (P&L) statements. This role requires a deep understanding of sales reports, key business metrics, and the ability to transform raw data into actionable insights. The ideal candidate will work closely with cross-functional teams to optimize reporting, improve data integrity, and support strategic decision-making through data-driven analysis.

Core Tasks

  • Develop, optimize, and maintain complex SQL queries for data extraction, transformation, and analysis.
  • Design and automate reporting dashboards to track sales performance and key business metrics.
  • Analyze and interpret P&L statements to provide strategic recommendations.
  • Work with stakeholders to identify data requirements and create tailored reports.
  • Ensure data integrity and accuracy across databases and reporting platforms.
  • Identify trends in sales, inventory, and financial performance to drive business improvements.

Must Haves

  • 3+ years of experience as an SQL Engineer, Data Analyst, or related role.
  • Advanced proficiency in SQL (query optimization, indexing, stored procedures).
  • Strong experience working with databases such as PostgreSQL, MySQL, SQL Server, or Oracle.
  • Familiarity with ETL processes and data warehousing platforms (e.g., Snowflake, BigQuery, Redshift).
  • Proficiency with BI and visualization tools like Looker, Power BI, or Tableau.
  • Experience with financial reporting, including interpreting and analyzing P&L statements.
  • Strong understanding of retail and sales performance metrics.
  • Ability to work independently in EST time zone hours.
  • Strong problem-solving skills and ability to communicate technical insights to non-technical stakeholders.

Nice to Have

  • Experience with Python or R for data analysis and automation.
  • Knowledge of cloud-based data services (AWS, GCP, or Azure).
  • Prior experience in a fast-paced startup or retail analytics environment.