Note: The job is a remote job and is open to candidates in USA. Ex Parte, Inc. is a company focused on providing data and insights for legal decision-making. They are seeking a Senior Data QA Engineer to take ownership of data quality, automate testing frameworks, and ensure data integrity throughout the ETL lifecycle.
Responsibilities
- Take ownership of end to end data quality
- Understand and Contribute to the event model design
- Build and automate testing frameworks around data ingestion pipelines
- Write complex SQL queries on tables with hundreds of millions of records and ensure data integrity is maintained throughout the ETL lifecycle
- Design test cases and write python/SQL scripts to validate data integrity and identify gaps and opportunities in our pipelines
- Track data issues and work with team leads from discovery to resolution
- Collaborate with the analytic teams to conduct data quality investigations, improve automation and tools
- Review current tools and enhance them to help with data integrity
Skills
- 5+ years of work experience in QA, preferably in data or relevant space
- Demonstrable knowledge, experience, skill, and proficiency with the following: Scrum/Agile methodologies, SDLC, Python (at least reading), SQL
- Experience with different facets of QA tests such as functional progression & regression, integration, performance, load, UAT, and operational readiness testing
- Must be self-motivated, able to work independently, and thrive in a fast-paced, multi-tasking, high productivity environment while maintaining excellent working relationships with people in a wide variety of functional areas
- Excellent verbal and written communication skills
- Applied experience with Databricks and/or Azure ML
- Strong coding abilities in one or more scripting languages like Python or SQL
- Understanding of compliance, security, and risk domains along with associated patterns and data elements
- Use of one of the following vendor reporting solutions: PowerBI or Tableau
- Understanding of product and services activation, use, and transaction models and data
- Understanding of statistical analysis and machine learning tools and practices
- Understanding of Cloud-centric data processing and visualization approaches including SQL and NoSQL databases with exposure to Azure SQL, Azure Cosmos DB, Data Factory, Synapse, Azure Data Lake, etc
- Familiarity with Agile software delivery including application lifecycle mgmt (Jira/Azure DevOps/VSTS, Git)
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