Senior Consultant.e/Manager - Lead Data Engineering
Tasks
- Build data pipelines batch microbatch streaming
- Define platform data and AI architecture patterns
- Design modern data and AI architectures
- Develop RAG pipelines and vector database integrations
- Ensure data quality and monitoring
- Implement MLOps and LLMOps workflows
- Implement data governance and security access
- Industrialize AI and GenAI use cases to production
- Lead pre sales technical scoping and estimations
- Lead squads and provide technical direction
- Mentor data engineers and conduct code reviews
- Orchestrate AI agent workflows with APIs and business systems
- Provide data observability for pipelines
Perks/Benefits
Skills/Tech-stack
AWS | Azure | Cloud infrastructure | Cloud infrastructure as code | Cloud platform | Data Engineering | Data Governance | Data Lake | Data Observability | Data Products | Data Quality | Data Warehouse | Data mesh | Databricks | Dataiku | Docker | Google Cloud | Google Cloud Platform | Infrastructure as Code | Kubernetes | LLM Observability | LLMOps | Lakehouse | Language model operations | Large Language Model | Large Language Model Operations | Learning operations | MLOps | Machine Learning | Machine Learning Operations | Model Operations | PySpark | Python | RAG | SQL | Snowflake | Terraform | Vector Database | “as-code”
Education
N/A
Roles
Data Engineer | Data Engineering | Data Engineering Manager | Engineer | Engineering | Engineering Manager | Lead | Lead Data | Lead Data Engineer | Lead Data Engineering | Manager | Senior Data Engineering | Senior Data Engineering Manager | Tech Lead | Tech Lead - Data Engineering | Tech Lead, Data
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