Data Quality Analyst (SQL & Python) | WFH!

KMC Solutions; Metro Manila; On-site; PHP 480,000 - 720,000; Full time

Job summary

KMC Solutions in the Philippines is seeking a Data QA / Data Analyst to ensure data quality across multiple databases and cloud platforms. The role requires strong SQL skills, knowledge of Python for testing, and experience with ETL/ELT processes.

You will collaborate with cross-functional teams to identify issues and implement improvements. The candidate should be comfortable reporting onsite 1–2 times per month and working with structured and unstructured data in data pipelines.

Qualifications

• Minimum 2 years of experience in Data Quality, Data QA, or Data Analysis.
• Strong SQL skills for data validation, querying, and analysis.
• Working knowledge of Python for data testing and automation.
• Solid understanding of data quality principles: Accuracy, Consistency, Validity.
• Experience working with ETL / ELT processes and data pipelines.
• Familiarity with structured and unstructured data.
• Knowledge of cloud platforms such as AWS or Azure.
• Experience with MongoDB databases.

Responsibilities

• Perform data quality validation to ensure data accuracy, completeness, consistency, and validity.
• Validate datasets using SQL and identify data issues, discrepancies, and anomalies.
• Develop and execute basic Python scripts for data testing and automation.
• Support validation of structured and unstructured datasets.
• Review and validate ETL/ELT data pipelines and data transformations.
• Work closely with cross-functional teams to resolve data quality issues.
• Ensure data integrity across databases and cloud-based platforms.
• Document findings, recommend improvements, and support continuous data quality initiatives.

Skills

Data QA / Data Quality

SQL

Python

Data validation principles

ETL/ELT

Structured and unstructured data

Cloud platforms (AWS/Azure)

MongoDB

Tools

Great Expectations

dbt Tests

Vector databases

RAG pipeline evaluation

Job description

• Must be willing to report onsite 1–2 times per month as needed

Experience Required

• Minimum 2 years of experience in Data Quality, Data QA, or Data Analysis

Key Responsibilities

• Perform data quality validation to ensure data accuracy, completeness, consistency, and validity.
• Validate datasets using SQL and identify data issues, discrepancies, and anomalies.
• Develop and execute basic Python scripts for data testing and automation.
• Support validation of structured and unstructured datasets.
• Review and validate ETL/ELT data pipelines and data transformations.
• Work closely with cross-functional teams to resolve data quality issues.
• Ensure data integrity across databases and cloud-based platforms.
• Document findings, recommend improvements, and support continuous data quality initiatives.

Qualifications:

Required

• Minimum 2 years of experience in Data Quality, Data QA, or Data Analysis.
• Strong SQL skills for data validation, querying, and analysis.
• Working knowledge of Python for data testing and automation.
• Solid understanding of data quality principles:
  • Accuracy
  • Consistency
  • Validity
• Experience working with ETL / 
• Familiarity with structured and unstructured data.
• Knowledge of cloud platforms such as AWS or Azure.
• Experience working with databases such as MongoDB.

Preferred Qualifications

• Experience with data validation frameworks (e.g., Great Expectations, dbt Tests).
• Familiarity with vector databases and RAG pipeline evaluation.
• Exposure to AI/ML or Large Language Model (LLM) systems.
• Experience evaluating AI-generated outputs.
• Background in healthcare or life sciences data.
• Experience working in an Agile environment.