Description

EPAM is a leading global provider of digital platform engineering and development services. We are committed to having a positive impact on our customers, our employees, and our communities. We embrace a dynamic and inclusive culture. Here you will collaborate with multi-national teams, contribute to a myriad of innovative projects that deliver the most creative and cutting-edge solutions, and have an opportunity to continuously learn and grow. No matter where you are located, you will join a dedicated, creative, and diverse community that will help you discover your fullest potential. We are looking for an experienced Senior Data Quality Engineer to join our remote team and lead a project focused on ensuring the accuracy and completeness of data in our organization. In this role, you will be responsible for designing, developing, and executing automated tests to validate data quality, as well as identifying and resolving data quality issues. You will work closely with cross-functional teams to ensure that data meets the organization's requirements and standards. If you have a passion for data quality and have a proven track record of designing and implementing automated tests, we want to hear from you. #LI-AP13 #EasyApply Technologies

Programming Languages: Python SQL - MSSQL, PostgreSQL, MySQL, Oracle Big Data - Hadoop, HDFS, Hive, Spark, Kafka, Flume, Sqoop NoSQL Cassandra, HBase, MongoDB Data Visualization: Tableau, Tibco Spotfire, Power BI ETL - MS SSIS, Talend, MicroStrategy Cloud - AWS/Azure/GCP - Storage; Compute; Networking; Identity and Security; Notebooks; Data Catalogs MDM tools Data Generation Test Management Tools: TestRail, Zephyr Performance Testing: JMeter CI/CD principles & tools: Jenkins Queues and Stream processing Version Control Systems: Git, SVN Responsibilities

Be responsible for data product testing and quality of deliverables on the project Data quality implementation and improving data quality as the main goal Establish data testing approach and test design, data quality checks across the data lifecycle Work on priorities to achieve better data quality on the project within a tight schedule Design and implement data testing strategy concerning system architecture and data flows Plan and estimate required resources to conduct data product/flow testing and validation concerning company/industry / governmental standards Design and develop a data quality framework according to the identified data product strategy (define critical data, controls, and quality targets, set thresholds and alerts, etc.) Understand, design, and implement automated data quality checks Requirements

3+ years of software engineering experience and practice in Data Management, Data Quality verification/Data Governance, Data Visualization testing, Data Integration Familiar with concepts of data ingestion pipelines, and data storage like OLTP databases, Data Warehousing, Data Lakes Understanding of the ETL process and test strategy for ETL Strong SQL experience Experience with scripting/automation Knowledge and practical experience in data validation Familiar with test documentation concepts, such as test strategies, test plans, etc Familiar with testing methods - TDD, BDT, DDT Analytical approach to problem-solving; excellent interpersonal and communication skills Experience in Data analysis & requirements validation Data-oriented personality; motivated, independent, efficient, and able to work under pressure with a solid sense for setting priorities Experience in direct customer communications Skills in infrastructure troubleshooting, support in performance tuning and optimization, bottleneck problem analysis Understanding of CI/CD principles Nice to have

Knowledge of Java , Scala, Bash, xpath Experience with big data technologies such as Hadoop, Spark, or Kafka Familiarity with cloud platforms such as AWS, GCP, or Azure Certifications in data quality or software engineering