Familiar with Scrum/Agile methodologies and SDLC processes.
Proficient in Python and SQL, with ability to read and write code.
Experience with various QA tests such as functional, regression, and performance testing.
Strong ability to work independently and maintain relationships across teams.
Responsibilities
Own and ensure end-to-end data quality processes.
Contribute to the design of event models and frameworks.
Automate testing for data ingestion pipelines.
Write and optimize complex SQL queries for large datasets.
Design test cases and scripts to identify data gaps and validate integrity.
Collaborate with analytics teams for data quality improvements.
Review and enhance current tools for better data integrity.
Benefits
Flexible working environment with opportunities for remote work.
Access to training and development resources.
Collaborative teamwork culture with cross-functional exposure.
Opportunities to influence tool and process enhancements.
Full Job Description
Job Description
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.
Qualifications
Minimum Qualifications
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
Preferred Qualifications
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).
