DQA Developer - Data Quality & Validation

Description :

- Perform data profiling, data cleansing, and data transformation to ensure data accuracy and consistency.

- Monitor and report on data quality metrics such as completeness, consistency, uniqueness, and accuracy.

- Design and automate data validation and quality-check workflows to improve efficiency and reliability.

- Integrate data quality checks into ETL pipelines and modern data platforms.

- Implement and support data quality, data profiling, and data governance frameworks.

- Collaborate with data engineers, analysts, and stakeholders to understand data requirements and quality standards.

- Develop Python-based scripts or utilities for data validation, automation, and reporting.

- Work with Databricks notebooks and contribute to solutions in a Databricks-based environment.

- Troubleshoot data quality issues and provide root-cause analysis and recommendations.

Required Skills & Qualifications :

- Hands-on experience in data profiling, data cleansing, and data transformation processes.

- Solid understanding of data quality dimensions including completeness, consistency, uniqueness, and accuracy.

- Experience in automating data validation and quality-check workflows.

- Familiarity with integrating data validation processes into ETL pipelines.

- Experience working with modern data platforms.

- Proficiency in Python for scripting, automation, and data validation tasks.

- Hands-on experience working with Databricks notebooks and Databricks environments.

- Strong analytical, problem-solving, and communication skills.

Good to Have :

- Exposure to cloud platforms (AWS, Azure, or GCP).

- Knowledge of SQL and data warehousing concepts.

- Experience working in Agile/Scrum environments.