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Senior Data Quality Engineer

Workday

based on 28 Reviews

4-8 years

Pune

1 vacancy

Senior Data Quality Engineer

Workday

posted 3mon ago

Flexible timing

Key skills for the job

+ 2 more

Designing and implementing data quality checks, identifying, and resolving data quality issues, collaborating with data engineers and product team to improve data pipelines, and developing data quality standards and best practices.
Collaborate with data engineers, analysts, and business stakeholders to understand data requirements and quality expectations.
Analyze architecture and designs to identify test automation strategies to provide full test coverage for new and/or existing data quality checks. Identify and articulate gaps in architecture or design which would lead to data quality issues. Goal here is to validate, automate and maintain high-quality data that supports informed decision-making and business operations.
Monitor and analyze data quality metrics to proactively identify issues and opportunities for improvement.
Establish data quality monitoring processes as part of CI/CD and tools to ensure ongoing compliance with quality standards.
Investigate root causes of data quality issues and work with relevant teams (upstream, downstream Analyst) to implement corrective actions.
Provide technical guidance and support to ensure data quality standards are integrated into all data-related projects and initiatives.
Work closely with Data Operations Support, Monitoring team to capture production data quality exceptions and mitigate business impact/risk
Document data quality processes, procedures, and standards for reference and training purposes.

Business Qualifications

Bachelors degree in Computer Science, Information Systems, or a related field; Masters degree preferred.
Proven experience as a Data Quality Engineer or similar role, with a minimum of 10 years in data quality management or data governance.
Solid understanding of data management concepts, including data profiling, data cleansing, and data integration.
Proficiency in SQL for data querying and manipulation. Develop and execute automated data quality tests using tools like SQL, Python (Pyspark), and data quality frameworks.
Experience with working in a cloud environment (AWS, GCP) preferred.
Experience with data warehousing solutions (Snowflake, Databricks, Redshift) preferred.
Experience with data integration and transformation tools (e.g. Snaplogic, Prophecy, dbt, Talend, etc.) a plus.
Experience with data quality monitoring tools (Acceldata, Tricentis) a plus.
Working knowledge of DevOps principles and CI/CD pipelines preferred.
Strong analytical skills with the ability to identify patterns, trends, and outliers in data.
Strong problem-solving skills and attention to detail.

Other Qualifications

Excellent communication and collaboration skills, with the ability to work effectively with cross-functional teams.
Proven ability to prioritize and manage multiple tasks in a fast-paced environment.
Certification in relevant technologies or data management disciplines is a plus.
Analytical mindset with the ability to think strategically and make data-driven decisions.