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We are looking for one Data Quality Engineer responsible for designing, implementing, and maintaining Data quality frameworks, validation processes, and monitoring solutions to ensure accuracy, completeness, and consistency of enterprise data. This role collaborates closely with Data Architects, Data stewards, and Data Governance teams to automate data validation, resolve data anomalies, and build trust in Data products.
Job Responsibility:
Designing, implementing, and maintaining Data quality frameworks, validation processes, and monitoring solutions
Ensuring accuracy, completeness, and consistency of enterprise data
Collaborating with Data Architects, Data stewards, and Data Governance teams
Automating data validation
Resolving data anomalies
Building trust in Data products
Providing operational monitoring and reporting on data quality through tools and indicators
Onboarding Data products
Supporting users in ensuring consistency, facilitating adoption and maintaining features backlog
Configuring quality rules, managing dashboards/KPIs, and running monitoring checks
Supporting governance officers with indicators
Automating checks
Acting as an advisor to Data Architects, Data Governance Officers, Data Product Owners and Managers
Requirements:
9+ years of experience in design and implement data quality frameworks to assess data accuracy, consistency, completeness, and validity
Strong experience of defining, documenting, and managing Data quality rules, metrics, and thresholds for key data domains
Strong experience of implementing automated validation and reconciliation processes across source and target systems
Strong expertise in Snowflake
Good Knowledge of SQL, and Data testing
In-depth knowledge of Data Governance, Sifflets, Data Quality, and MDM frameworks
Experience of working with Python
BE / B.Tech/ MS/ M.Tech/ MCA
Excellent documentation skills
Strong stakeholder management and Communication skills
What we offer:
Commitment to fighting against all forms of discrimination
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