We are seeking a knowledgeable Senior Data Quality Engineer to join our team and ensure the accuracy, reliability, and efficiency of our data systems and workflows. In this role, you will lead impactful data quality initiatives, utilizing advanced technologies to drive meaningful outcomes. If you are passionate about enhancing data processes and enjoy working with innovative solutions, this is an opportunity to shape the future of our data operations.
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