Data Product Wrangler

3 days ago

Gurugram Haryana, India Invokhr Full time

**KEY ACCOUNTABILITIES**
- Data Discovery & Analysis: Perform data discovery to identify and understand data sources, data structures, and key entities within the business domain; document the data landscape and insights.
- Transformation Mapping: Map data transformations and create clear documentation of data flows for transparency.
- Data Testing & Quality Assurance: Conduct data profiling and testing to validate data quality, accuracy, and completeness. And collaborate with data quality teams to monitor data health, identify inconsistencies, and resolve data-related issues proactively.
- Data Profiling & Metadata Management: Profile data to assess its characteristics, distribution, and potential issues, facilitating data usage by other teams. And contribute to metadata management by documenting data definitions, data lineage, and business context for easy access and understanding.
- Collaboration & Communication: Work closely with business stakeholders and data community to understand data requirements and provide necessary insigh

**FUNCTIONAL / TECHNICAL SKILLS**
- Proficiency in Python, SQL or similar tools for in-depth data analysis, profiling, and validation.
- Strong understanding of Insurance domain business processes and an ability to align data insights with business needs.
- Experience in documenting and mapping data transformations and flows across various systems.
- Excellent skills in documenting data processes, definitions, and mappings, and the ability to communicate effectively with non-technical stakeholders.
- Knowledge of data quality assessment techniques and data testing practices to ensure data integrity.
- Strong working knowledge of Azure and databricks.
- Extensive experience in production grade data solutions and complex delivery.

**DECISION MAKING AUTHORITY/ IMPACT**
- Authority to lead the design of data products, ensuring alignment with enterprise objectives and governance standards.
- Responsibility to drive collaboration across data, engineering, and business teams, ensuring the seamless integration and usability of data products.

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