Papigen Private Limited
Website:
papigen.com
Job details:
Role Overview
We are looking for an experienced
Data Quality Engineer to design, implement, and maintain enterprise data quality solutions across cloud-based data platforms. The ideal candidate will have strong expertise in
SQL, Databricks, ETL/ELT pipelines, Azure, and
Monte Carlo Data Observability. This role will focus on improving data reliability, implementing data quality rules, monitoring data health, and collaborating with engineering and governance teams to ensure trusted data across the organization.
Key Responsibilities
- Design and implement enterprise Data Quality frameworks and validation rules.
- Configure and manage Monte Carlo Data Observability for monitoring data quality, freshness, lineage, and pipeline health.
- Develop and optimize SQL queries for data validation, profiling, and analysis.
- Build and support ETL/ELT pipelines using modern data engineering practices.
- Work with Databricks for batch and near real-time data processing.
- Analyze large datasets and identify data quality issues and root causes.
- Collaborate with Data Engineers, Architects, and Business teams to improve data quality and governance.
- Support Collibra and metadata management initiatives.
- Monitor data pipelines, troubleshoot failures, and ensure timely issue resolution.
- Implement data quality monitoring, reporting, and continuous improvement processes.
- Participate in Agile ceremonies and contribute to technical documentation.
Required Skills
- 5+ years of experience in Data Quality Engineering or Data Engineering.
- Strong hands-on experience with Monte Carlo Data Observability (Mandatory).
- Strong SQL skills with experience handling large datasets.
- Hands-on experience with Databricks.
- Experience with Data Quality tools and implementation of data quality frameworks.
- Experience with ETL/ELT tools and pipelines.
- Experience working with Azure cloud data platforms.
- Experience with relational and NoSQL databases.
- Familiarity with Collibra and data governance concepts.
- Understanding of Data Warehouses, Data Lakes, and Lakehouse architectures.
- Knowledge of Dimensional and Relational Data Modeling.
- Strong analytical, troubleshooting, and communication skills.
Nice to Have
- Programming experience in Python, Scala, or Java.
- Experience with orchestration tools such as Airflow or Control-M.
- Knowledge of Data Governance, Metadata Management, and Data Lineage.
- Experience in Banking or other regulated environments.
- Certifications in Azure, AWS, or CDMP.
Skills: python,azure,azure cloud,nosql,collibra,data lakes,data quality,monte carlo,scala,lakehouse,sql,etl,databricks,data warehouse,java
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