Senior Data Engineer
Tasks
- Bridge gap between product building and business problem solving
- Define project directions within strategic goals
- Define service level objectives and ensure system resilience
- Design and build data integration and storage systems
- Design data infrastructure for analytics and AI
- Develop high-quality, enterprise-standard code
- Develop resilient enterprise data solutions
- Identify patterns and hand off solutions to platform engineers
- Implement data validation and governance frameworks
- Influence multiple teams
- Make architectural trade-offs
- Manage discovery-to-scale data pipeline
- Navigate high complexity and ambiguity
- Prototype and build end-to-end data applications
Perks/Benefits
- Access to AI platforms
- Challenging work
- Diverse culture
- Growth opportunities
- High-profile clients
- Hybrid work model
- Impactful projects
- Innovative environment
- Supportive management
Skills/Tech-stack
AI tools | AWS | Application development | Azure | CI/CD | Cloud Platforms | CloudFormation | Code Quality | Code quality and testing | Data Modeling | Data Normalization | Data Pipelines | Data Validation | Data application development | ELT | ETL | End to End | End-to-end data application development | GCP | MLOps | Query performance | SRE | Scalable System Design | Schema migrations | Service Level | Service-Level Objectives | System Resilience | System design | Terraform
Roles
Regions
Countries
States
Cities
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