Data QA Engineer

This is a fully remote position, open to applicants in Qatar.

📋 Description

• Take full responsibility for ensuring data quality from start to finish.

• Comprehend and contribute to the design of the event model.

• Develop and automate testing frameworks for data ingestion pipelines.

• Craft complex SQL queries on tables containing hundreds of millions of records, ensuring data integrity is upheld throughout the ETL lifecycle.

• Design test cases and create Python/SQL scripts to validate data integrity while identifying gaps and opportunities within our pipelines.

• Monitor data issues and collaborate with team leads from identification to resolution.

• Partner with analytical teams to perform data quality investigations, enhance automation, and improve tools.

• Evaluate existing tools and upgrade them to support data integrity.

⛳️ Requirements

• Over 5 years of experience in Quality Assurance, ideally in data or a related field.

• Proven knowledge and skills in Scrum/Agile methodologies, Software Development Life Cycle (SDLC), Python (at least at a reading level), and SQL.

• Familiarity with various types of QA tests, including functional progression & regression, integration, performance, load, User Acceptance Testing (UAT), and operational readiness testing.

• Must be driven, capable of working independently, and excel in a fast-paced, multi-tasking, high-productivity environment while maintaining strong working relationships across various functional areas.

• Exceptional verbal and written communication abilities.

• Practical experience with Databricks and/or Azure ML (Preferred).

• Strong coding skills in one or more scripting languages like Python or SQL (Preferred).

• Understanding of compliance, security, and risk domains, along with relevant patterns and data elements (Preferred).

• Experience with one of the following vendor reporting solutions: PowerBI or Tableau (Preferred).

• Knowledge of product and service activation, usage, transaction models, and data (Preferred).

• Familiarity with statistical analysis and machine learning tools and practices (Preferred).

• Understanding of cloud-centric data processing and visualization strategies, including SQL and NoSQL databases, with exposure to Azure SQL, Azure Cosmos DB, Data Factory, Synapse, Azure Data Lake, etc. (Preferred).

• Knowledge of Agile software delivery, including application lifecycle management tools like Jira/Azure DevOps/VSTS and Git (Preferred).

🏝️ Benefits

• All your information will be kept confidential according to EEO guidelines.