Data Engineer
INR 1500K-2600K (estimate) Mid-level Full Time
Tasks
- Architect AI ready data platform components for ML consumption
- Architect scalable cost effective data platforms
- Build and maintain feature stores on Vertex AI for low latency serving
- Build pipelines for embedding generation and vector store population and RAG retrieval
- Define SLAs implement alerting and lead incident resolution
- Define reusable engineering patterns pipeline templates transformation standards and naming conventions
- Design CI CD pipelines with automated testing and deployment gates
- Design data models using dimensional and normalization and data vault
- Drive DataOps practices with automated testing data contracts and observability
- Ensure data security encryption and governance compliance
- Execute testing strategies for regulated workloads with parallel validation
- Implement SCD strategies and historical data management
- Lead code reviews and improve quality testability and maintainability
- Lead end to end design and delivery of data engineering solutions on GCP
- Mentor junior engineers through pairing and feedback
- Migrate legacy data structures to GCP with validation
- Monitor and optimize GCP costs and implement efficiency improvements
- Provision and govern cloud infrastructure with Terraform
Perks/Benefits
- N/A
Skills/Tech-stack
Airflow | BigQuery | CI/CD | Cloud Build | Cloud Composer | Cloud Composer Airflow | Cloud Storage | Cloud platform | Composer (Airflow) | DBT | Data Contracts | Data Governance | Data Modeling | Data Vault | DataOps | Dataflow | Dataform | Dataplex | Dimensional Modeling | Embeddings | Encryption | Feature Store | GitHub Copilot | Google Cloud | Google Cloud Platform | Google Gemini | Kimball | LLM-Ops | Observability | PubSub | Python | RAG | SCD | SQL | Terraform | Third Normal Form | Vector Databases | Vertex AI
Education
N/A
Roles
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