17 Aumni Techworks Jobs

Job Summary - QA Specialist, Data & Analytics:

We re looking for a meticulous and detail-oriented QA Specialist who is passionate about data quality. You will collaborate with our analytics team to develop and execute comprehensive QA processes, validate data pipelines, and automate recurring QA processes. Your work will be key to ensuring our data and analytics deliverables meet the highest standards of accuracy and reliability.

Responsibilities:

Develop and execute comprehensive QA processes for data and analytics deliverables.

Validate the entire data pipeline, including data sources, ETL processes, extracts, calculations, visualizations, and application interfaces.

Perform functional, regression, performance, and tolerance-range testing across reports and data systems.

Simulate end-user journeys to ensure a seamless user experience with analytics outputs.

Validate application tracking functionality (data collection through application usage).

Validate calculations and metrics in Tableau, Power BI, and other BI tools.

Conduct database validations using SQL (Oracle, Big Query) and NoSQL (MongoDB) systems.

Automate recurring QA processes in the analytics/BI environment when feasible.

Identify and document data quality issues and discrepancies.

Collaborate with cross-functional teams, including data engineers, BI developers, and product managers, to ensure analytics quality.

Experience:

3+ years of experience in QA, data validation, or analytics testing.

Hands-on experience BI tools environment testing.

Proficiency in SQL (Advantage: experience with Oracle and Big Query databases).

Experience with NoSQL databases (Advantage: MongoDB). Technical Skills.

Familiarity with regression testing and simulating user interactions with BI tools.

Nice-to-Have Qualifications:

Advantage: Familiarity with scripting languages like R or Python.

Advantage: Experience in automation testing within analytics or BI environments.

Advantage: Experience in Databricks environment. Collaboration and Leadership:

Excellent communication skills with the ability to collaborate effectively across departments.

Strong ability to present complex findings to both technical and non-technical audiences.