We are looking for an experienced Senior Data Quality Engineer to join our team and take responsibility for ensuring the accuracy, reliability, and performance of our data systems and workflows. In this role, you will lead key initiatives to improve data quality, leveraging advanced technologies to deliver impactful results. If you are passionate about refining data processes and enjoy working with cutting-edge solutions, this position offers the chance to shape the future of our data infrastructure.
Responsibilities
Create and implement data quality strategies to ensure consistent accuracy across data systems and products
Lead initiatives to improve data workflows by incorporating best practices across teams and projects
Develop and apply advanced testing frameworks and methodologies to meet enterprise data quality standards
Efficiently manage complex data quality tasks, ensuring prioritization and delivery under tight deadlines
Design testing strategies tailored to evolving system architectures and data pipeline requirements
Provide recommendations on resource allocation and testing priorities that align with compliance and business needs
Establish and refine governance frameworks to ensure alignment with industry standards
Build and optimize automated validation pipelines to support production environments
Collaborate with cross-functional teams to resolve infrastructure challenges and improve system performance
Mentor junior engineers and maintain comprehensive documentation of testing processes and strategies
Requirements
At least 3 years of professional experience in Data Quality Engineering or related roles
Advanced proficiency in Python for data validation and workflow automation
Expertise in Big Data platforms such as Hadoop tools (HDFS, Hive, Spark) and modern streaming technologies like Kafka, Flume, or Kinesis
Hands-on experience with NoSQL databases like Cassandra, MongoDB, or HBase for managing large-scale datasets
Proficiency in data visualization tools such as Tableau, Power BI, or Tibco Spotfire for analytics and reporting
Extensive experience with cloud platforms like AWS, Azure, or GCP, with knowledge 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 like 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
Deep understanding of testing frameworks such as TDD, DDT, and BDT for data-focused environments
Experience implementing CI/CD pipelines using tools like Jenkins or GitHub Actions
Strong analytical and problem-solving abilities, with the capability to derive actionable insights from complex datasets
Excellent verbal and written communication skills in English (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 knowledge of XPath for data validation and transformation workflows
Proficiency in designing custom data generation tools and synthetic data techniques for testing scenarios