Senior Data Quality Engineer |REMOTE

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Senior Data Quality Engineer -REMOTE

PURPOSE

The Senior Data Quality Engineer will help develop and implement an automated testing framework and test process that can be used for testing client's Group Data Platform. This Data Platform testing framework will be used in agile scrum Development efforts, regression and continuous testing efforts. In addition, this position will utilize appropriate test tools, process and practices as defined by the QA Leaders for functional, systems-integration, ETL migration testing, as well as building in quality standards throughout the SDLC to avoid defects and minimize rework and waste.

Essential Duties, Responsibilities & Outcomes

Support design, build and implement automated test framework and tools to automate the Data platform services and applications.

Develop and implement testing practices and tools as part of the framework which ensure releases are defect-free and perform at or better than expected levels

Provide technical directions, mentor quality assurance team as well as the scrum teams on effective testing practices, including test driven development

Use SQL queries and analyze log files to test various ETL and data pipelines

Develop data quality testing plans and scripts. Perform data validity, accuracy and integrity test across different components of the Data platform.

Automate the regression testing and ensure quality practices are built into the SDLC and DevOps practices

Ensure that business requirements are fully met before each release; certify releases for quality and completeness of functionality

Closely collaborate with other technology and business users to ensure business and technical requirements are understood and met

Minimum Qualifications:

Bachelor s Degree, Computer Science, Engineering or related is requirement

5+ years of work experience in QA, preferably in data science or relevant space

5+ yrs applied experience writing complex SQL / Spark SQL on large data sets to transform data, facilitate accurate and reliable data analytics across various functions.

Strong coding abilities in Python, PySpark, Pandas or other similar tools for large scale data processing, data quality checks, validations and analysis.

Advanced proficiency in SQL and familiarity with other relational data via Oracle, Postgres, and/or SQL Server

Proficiency with industry recognized ETL/ELT testing methodologies, techniques, processes and standards

Hands-on experience with Databricks in AWS environment

Experience in automation of data pipelines, data services, cloud data warehouses, business intelligence, and machine learning platforms

Experience in developing Databricks notebook to test data quality and business requirements

Passionate and highly skilled in utilizing programming languages and analytics tools/technologies to validate products, machine learning models, data pipelines, and data deliverables