Data & AI - Data Engineer
Tasks
- Build and maintain lakehouse or warehouse transformation layer
- Build and operate production data pipelines and platforms
- Deliver data architecture standards and reusable pipeline components
- Design and maintain governed semantic layer
- Design governed audit ready pipelines and controls
- Implement data governance privacy access controls and de identification
- Ingest and integrate data from source systems using batch and streaming
- Mentor junior data engineers
- Model data for business intelligence and artificial intelligence consumers
- Own data quality master data and lineage with validation and golden records
- Prepare artificial intelligence ready data including embeddings source data and retrieval corpora
Perks/Benefits
Skills/Tech-stack
Airflow | Amazon Web Services | Apache Flink | Apache Iceberg | Apache Kafka | Atlan | Change Data Capture | Chunking | Cloud platform | Collibra | Cube | DBT | DBT Cloud | Dagster | Data Capture | Data Catalog | Data Contracts | Data Governance | Data Lineage | Data Management | Data Quality | Data Validation | Data Vault | Databricks | Dbt tests | Delta Lake | Dimensional Modeling | Embeddings | Entity Resolution | Google Cloud | Google Cloud Platform | Graph Databases | Great Expectations | Infrastructure as Code | Knowledge graphs | LookML | Master Data | Master Data Management | Microsoft Azure | Neo4j | OpenMetadata | PGVector | Pinecone | Privacy Compliance | Python | Qdrant | Resource Description Framework | Resource description | Retrieval-Augmented Generation | SPARQL | SQL | Snowflake | Terraform | Vector Databases | Weaviate | Web Services | “as-code”
Education
N/A
Roles
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