Julieta Tarkhanyan

I provide professional verification for Data Analyst and Data Engineer candidates based on real working experience in data field. My focus is not only on theory, but also on practical skills, problem solving, and business understanding. In many cases, candidates know tools and theory, but they cannot work with real data or solve real problems. My goal is to check if candidate is ready to work in real projects with messy data, unclear requirements, and production environments. I evaluate candidates in structured way and give clear feedback about their level, strengths, and weaknesses. Data Analyst Verification What I Check 1. SQL Skills I check candidate’s ability to work with data using SQL. This includes: a. Writing queries with joins, aggregations, CTE, and window functions b. Filtering, grouping, and transforming data c. Working with incomplete or inconsistent data Good candidate should not only write queries, but also understand logic behind them and structure queries correctly. 2. Analytical Thinking I check how candidate approaches problems: a. Can they break business problem into data questions b. Can they identify trends, anomalies, and patterns c. Can they find root cause of issue Strong candidate explains not only what is happening, but also why it is happening. 3. Business Understanding Data analyst should understand business side, not only data: a. Knowledge of KPIs and metrics b. Understanding how data connects to business results c. Ability to give useful insights Candidate should be able to translate data into simple business language. 4. Data Visualization & Communication I check how candidate presents data: a. Experience with tools like Tableau or Power BI b. Ability to create clear dashboards c. Ability to explain results to non-technical people Clear communication is very important for analyst role. Data Engineer Verification What I Check 1. ETL & Data Pipelines I check understanding of data flow: a. How data moves from source systems to final