Diverse LynxRemote
Azure Data Lake Engineer
United States of America
Full Time
3 weeks ago
H1B Sponsor Likely
Key skills
Azure Data LakeData Feed EngineeringData Feed ReviewData Structure OptimizationData Pipeline AutomationData Quality ChecksData DocumentationData LineageData GovernanceEntity Relationship Model DevelopmentData LakeAzureRepository
About this role
Diverse Lynx is a company that values diversity and equal opportunity in the workplace. They are seeking an Azure Data Lake Engineer to optimize data feeds, enhance data quality, and support the MDL community through various engineering tasks.
Responsibilities:
- Assess existing MDL data tables and create a structured inventory
- Conduct data feed reviews with the MDL community
- Improve data structures, performance, and documentation
- Support the identification of relevant Marketing & non Marketing data products
- Implement and test new data feeds; ensure quality and consistency
- Align with data stakeholders and support enablement
- Replace manual uploads with automated pipelines
- Develop concepts and PoCs for data quality checks (top 20 tables)
- Execute in depth quality reviews and implement corrective actions
- Document lineage, transformations, and table-level metadata
- Set up data dictionaries, PII-handling concepts, and taxonomy standards
- Contribute to ER model development and artefact standardization
- Coordinate across the MDL community
- Support access requests, platform education, and use-case repository updates
Requirements:
- 3-7 years of experience required
- Assess existing MDL data tables and create a structured inventory
- Conduct data feed reviews with the MDL community
- Improve data structures, performance, and documentation
- Support the identification of relevant Marketing & non Marketing data products
- Implement and test new data feeds; ensure quality and consistency
- Align with data stakeholders and support enablement
- Replace manual uploads with automated pipelines
- Develop concepts and PoCs for data quality checks (top 20 tables)
- Execute in depth quality reviews and implement corrective actions
- Document lineage, transformations, and table-level metadata
- Set up data dictionaries, PII-handling concepts, and taxonomy standards
- Contribute to ER model development and artefact standardization
- Coordinate across the MDL community
- Support access requests, platform education, and use-case repository updates