Data QA Engineer

Job Code: MACIN10156

Role: Data QA Engineer

Type of Commute: Remote

Skill Set: Snowflake Testing (Data Modeling, ETL & ELT), RDBMS, AWS, Python Basic

Desired Industry Experience: 7

Role Description:

Title: Data QA Engineer

Desired Industry Experience: 7+ years

Key Responsibilities:

• Develop and execute comprehensive test plans to validate data as it moves through the pipeline from Snowflake to other sources and vice versa.
• Monitor and validate ETL processes to ensure data is accurately and efficiently loaded.
• Automate data validation and data quality checks within the data pipeline using Soda.io, SQL, Python, and Snowflake tools.
• Track, document, and manage data quality issues across the data pipeline and within Snowflake.
• Collaborate with data engineers and pipeline developers to resolve data discrepancies and enhance data quality.
• Document test plans, cases, and outcomes for data processes.
• Regression testing of data platform.

Desired Skills:

Must have skills:

• Hands-on testing experience with Snowflake, including data modeling, ETL and ELT processes.
• Expertise in data validation, query optimization, and data management best practices in data sources/pipeline.
• Experience with data pipeline tools and frameworks, and their integration with Snowflake.
• Experience with cloud platforms, preferably AWS and their data services.
• RDBMS, Advanced SQL (including joins, subqueries and writing complex queries)
• Basic knowledge of AWS Airflow and Soda.io.
• Basic knowledge on Python scripting.

Added advantage skill set:

• AWS Devops CI/CD
• Experience with Agile development and delivery – Scrum/Kanban methodologies
• Experience within pharma/healthcare sector
• Certification in Snowflake (e.g., SnowPro Core)
• Experience with other cloud platforms (e.g. Azure, Google Cloud) and their data services.