Data Quality Engineer – Python / SQL / ETL

Location: Bonifacio Global City (BGC), Taguig
Experience: 2+ years
Work Setup: Hybrid

Job Overview

We are looking for an experienced Data Quality Engineer to ensure the accuracy, reliability, integrity, and usability of enterprise data.

The role combines Data Quality, Data Engineering, ETL, Python, SQL, data validation, automation, and data governance. You will design data quality rules, automate validation and testing, monitor data quality metrics, investigate data issues, and collaborate with Data Engineers and business teams to deliver trusted data solutions.

Key Responsibilities

• Design, implement, and maintain data quality rules and validation frameworks.
• Develop automated data validation and testing for data pipelines and ETL processes.
• Perform data profiling to identify inconsistencies, anomalies, duplicates, and data integrity issues.
• Monitor data quality metrics and investigate data anomalies.
• Identify root causes of data quality issues and work with Data Engineers and business teams to resolve them.
• Design, build, and maintain scalable and secure data pipelines and ETL workflows.
• Develop Python scripts and programs to automate data processing, validation, and quality checks.
• Write and optimize SQL queries for data analysis, validation, reconciliation, and troubleshooting.
• Ensure data complies with established governance, privacy, security, and regulatory requirements.
• Develop and maintain data models, databases, and data structures as required.
• Support data integration and transformation processes.
• Create reports, dashboards, and data visualizations to communicate data quality insights.
• Document data quality standards, rules, processes, and best practices.
• Collaborate with Data Engineers, Analysts, Business Teams, and other stakeholders to understand data requirements and improve data processes.

Non-Negotiable Requirements

• Minimum 2 years of experience in Data Engineering, Data Quality, Data Analytics, or a related field.
• Hands-on experience with Python.
• Proficiency in SQL.
• Experience with ETL / Data Flows / Data Pipelines.
• Hands-on experience developing automated data validation and quality checks.
• Experience with data profiling, anomaly detection, data reconciliation, and root-cause analysis.

Technical Skills

Data Engineering & Quality

• Python
• SQL
• ETL / ELT
• Data Pipelines
• Data Validation
• Data Profiling
• Data Quality Rules
• Data Testing
• Data Governance

Data Processing

• pandas
• Apache Spark
• dplyr
• Hadoop / Hive

Databases & Data Platforms

• SQL and NoSQL
• MongoDB
• Snowflake
• AWS Redshift
• Other Big Data / Data Warehouse platforms

Cloud

• AWS
• Azure
• GCP
• AWS Glue
• AWS Lake Formation

Visualization

• Power BI
• Tableau
• Amazon QuickSight
• Google Data Studio
• Plotly
• Dash
• Matplotlib

Nice-to-Have

• Experience with Apache NiFi.
• Experience with AWS Glue and AWS Lake Formation.
• Experience with Apache Spark / Hadoop.
• Experience with Snowflake or Amazon Redshift.
• Knowledge of Machine Learning tools such as scikit-learn.
• Experience with data visualization libraries and frameworks.
• Knowledge of data privacy, security, and regulatory requirements.