Senior Data Quality Automation Engineer

As Data Quality Engineer, you are responsible for:

Defining Quality Metrics

Defining quality standards and metrics for the current project/product. Working with all stake holders to ensure that the quality metrics is reviewed, closed and agreed upon. Create a list of milestones and checkpoints and set measurable criteria’s to check the quality on timely basis.

Defining Testing Strategies

Defining processes for test plan and several phases of testing cycle. Planning and scheduling several milestones and tasks like alpha and beta testing. Ensuring all development tasks meet quality criteria through test planning, test execution, quality assurance and issue tracking. Work closely on the deadlines of the project Ensure, you are focusing on automation along with manual testing. Keep raising the bar and standards of all the quality processes with every project. Thinking of continuous innovation. Review test strategies and see that all the various kinds of testing like unit, functional, performance, stress, acceptance etc. are getting covered.

Managing Risks

Understanding and defining areas to calculate the overall risk to the project. Creating strategies to mitigate those risks and take necessary measures to control the risks. Communicating or creating awareness to all the stake holders for the various risks Understand & review the current risks and escalate.

Process improvements

Challenge yourself continuously to move towards automation for all daily works and help others in the automation. Create milestones for yearly improvement projects and set. Work with the development team to ensure that the quality engineers get apt support like automation hooks or debug builds where ever and whenever possible

5-8 years of strong experience in QA/testing or application development

Strong in Database and ETL testing

Strong at preparing the test plan and ensure that test plans get reviewed by all stakeholders and strong in peer reviews.

Strong command of Essential technologies: SQL scripting, PL/SQL.

must have strong skills in writing complex and automated SQL scripts

ETL Testing from various feeds on server (S3, SQL ,HIVE, Data Bricks, Snow Flake) using different testing strategy to ensure the data quality and data consistency, timeliness

Hadoop & Big Data Concepts and Data validation on HIVE tables

Having knowledge on large-scale data processing languages like pyspark is a plus.

Strong command of any Programmatic Language (Python /Java preferred)

Knowledge of API Testing

Proficient with software development lifecycle (SDLC) methodologies like Agile, QA methodologies, defect management system, and documentation.

Experience in automation, automation frameworks and automation delivery preferred.

Good at setting Quality standards in various new testing technologies in the industry.

Good at identifying and defining areas to calculate the overall risk to the project and Creating strategies to mitigate those risks and escalate as necessary.

Excellent analytical and communication skill is required

Python/Java/Any Scripting,

Azure/AWS