Senior Consultant.e/Manager - Lead Data Engineering
Tasks
- Build data pipelines batch microbatch and streaming
- Conduct code reviews and mentor developers
- Define and implement modern data architectures
- Deploy and orchestrate agentic AI workflows
- Design and evolve data and AI platforms
- Design and operate RAG pipelines and vector databases
- Develop and operationalize AI and GenAI use cases
- Establish data governance catalogs lineage and access security
- Implement MLOps and LLMOps best practices
- Implement data quality tests monitoring and schema management
- Lead technical discovery and estimates for pre sales
- Package models and automate ML workflows
- Secure model API calls
- Set up LLM observability and prompt management
Perks/Benefits
Skills/Tech-stack
AWS | Azure | Azure Fabric | Bicep | CloudFormation | Data Architecture | Data Catalog | Data Contracts | Data Engineering | Data Governance | Data Lake | Data Lineage | Data Observability | Data Products | Data Quality | Data Warehouse | Data mesh | Databricks | Dataiku | Docker | GenAI | Google Cloud | Kubernetes | LLM Observability | LLMOps | Lakehouse | MLOps | Machine Learning | Medallion Architecture | Palantir Foundry | PySpark | Python | RAG | Retrieval-Augmented Generation | SQL | Snowflake | Terraform | Vector Database
Education
N/A
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