Role Overview

Join a dynamic team as a Senior Data Quality Engineer, where you'll enhance data accuracy and drive quality initiatives using advanced technologies. Shape the future of our data operations with your expertise in data quality strategies and cutting-edge tools.

Responsibilities

• Develop and implement data quality strategies to maintain accuracy and reliability across data systems and products.
• Lead efforts to enhance data quality by embedding best practices into team workflows and processes.
• Design and execute advanced testing methodologies and frameworks to ensure enterprise-level data quality standards are met.
• Manage complex data quality tasks efficiently, prioritizing under tight deadlines and competing requirements.
• Create tailored testing strategies aligned with evolving system architectures and data pipeline needs.
• Provide guidance on resource allocation and prioritize testing efforts to meet compliance and business objectives.
• Establish and continuously improve governance frameworks to ensure adherence to industry standards.
• Develop and scale automated validation pipelines to support production environments.
• Work collaboratively with cross-functional teams to troubleshoot infrastructure challenges and optimize system performance.
• Mentor junior team members and maintain detailed documentation of testing methodologies and strategies.

Requirements

• At least 3 years of professional experience in Data Quality Engineering or related fields.
• Advanced skills in Python for data validation and automation workflows.
• Expertise in Big Data platforms such as Hadoop tools (HDFS, Hive, Spark) and modern streaming technologies like Kafka, Flume, or Kinesis.
• Practical experience with NoSQL databases such as Cassandra, MongoDB, or HBase for managing large datasets.
• Proficiency in data visualization tools like Tableau, Power BI, or Tibco Spotfire for analytics and decision-making support.
• Extensive experience with cloud services such as AWS, Azure, or GCP, with an understanding of multi-cloud architectures.
• Advanced knowledge of relational databases and SQL technologies like PostgreSQL, MSSQL, MySQL, and Oracle in high-volume environments.
• Proven ability to implement and scale ETL processes using tools such as Talend, Informatica, or similar platforms.
• Familiarity with MDM tools and performance testing applications like JMeter.
• Strong experience with version control systems like Git, GitLab, or SVN, and automation for large-scale systems.
• Comprehensive understanding of testing frameworks such as TDD, DDT, and BDT for data-focused systems.
• Experience with CI/CD pipeline implementation using tools like Jenkins or GitHub Actions.
• Strong analytical and problem-solving skills, with the ability to extract actionable insights from complex datasets.
• Excellent verbal and written English communication skills (B2 level or higher), with experience engaging stakeholders.

Nice to Have

• Experience with additional programming languages like Java, Scala, or advanced Bash scripting for production-level solutions.
• Advanced understanding of XPath for data validation and transformation processes.
• Expertise in creating custom data generation tools and synthetic data techniques for testing scenarios.

We Offer

• International projects with top brands.
• Work with global teams of highly skilled, diverse peers.
• Healthcare benefits.
• Employee financial programs.
• Paid time off and sick leave.
• Upskilling, reskilling and certification courses.
• Unlimited access to the LinkedIn Learning library and 22,000+ courses.
• Global career opportunities.
• Volunteer and community involvement opportunities.
• EPAM Employee Groups.
• Award-winning culture recognized by Glassdoor, Newsweek and LinkedIn.