Data Analyst (IT Space) at KINZ Global Consult

Company Hiring: KINZ Global Consult
Job Title: Data Analyst
Job Field: Data, Business Analysis and AI, ICT / Computer 
Qualification Needed: BA/BSc/HND
Job Type: Full Time, Remote
Job Location: All States

Responsibilities

• Develop and execute data validation checks to ensure accuracy, completeness, and consistency of datasets.
• Support ETL and data pipeline testing by verifying record counts, transformations, and joins.
• Write and optimize complex SQL (PosgreSQL) queries to validate data transformations, aggregations, and business rules.
• Use Excel (advanced functions, pivot tables, charts, macros) to analyze data and prepare reports for stakeholders.
• Partner with developers, QA engineers, and business teams to investigate discrepancies and improve data quality processes.
• Perform root cause analysis on data anomalies and propose corrective actions.
• Build and maintain data quality dashboards, reports, and documentation.
• Translate business requirements into data requirements and validation logic.
• Assist in creating and maintaining metadata, data dictionaries, and data lineage documentation. Contribute to a culture of data governance, accuracy, and accountability.

Experience

• (4+ years) as a Data Analyst, Business Analyst, or similar role in data-heavy environments.
• Strong SQL expertise (joins, window functions, aggregations, subqueries, performance tuning).
• Advanced Excel skills (pivot tables, VLOOKUP/XLOOKUP, INDEX/MATCH, conditional formulas, macros preferred).
• Proven ability to identify and resolve data quality issues and inconsistencies.
• Familiarity with relational databases (PostgreSQL (most important), MySQL, SQL Server, etc.).
• Strong understanding of data integrity, validation, and governance principles.
• Ability to work with large, complex datasets under tight deadlines.
• Strong communication skills to collaborate with technical and non-technical stakeholders.

Nice-to-Have Skills:

• Experience with data visualization tools (Tableau, Power BI, Grafana).
• Knowledge of statistical methods for data validation and anomaly detection.
• Exposure to ETL processes and data pipeline monitoring.
• Familiarity with Python or R for data cleaning and analysis.
• Experience with big data platforms (ClickHouse, Hadoop, Spark).

How to Apply