Senior Data Engineer
Tasks
- Build batch streaming and near real time pipelines
- Build data models for analytical and operational use
- Collaborate with data scientists ML engineers analysts and stakeholders
- Create RAG and vector based data pipelines
- Create data serving layers APIs and feature inputs
- Design data platforms
- Develop lakehouse architectures and medallion layering
- Enable datasets for analytics machine learning and causal modeling
- Establish data observability monitoring and SLA tracking
- Implement data governance lineage quality and access control
- Implement data ingestion transformation and curation
- Optimize pipelines for performance, scalability, and cost
- Orchestrate data workflows and automation
Perks/Benefits
- Career advancement
- Hybrid work options
- Learning and development programs
- Professional development programs
- Remote work options
- Training programs
Skills/Tech-stack
ABAC | Airflow | Amazon Web Services | Apache Spark | Azure Fabric | CI/CD | Cloud platform | DBT | Data Governance | Data Lineage | Data Modeling | Data Quality | Databricks | Delta Lake | Event Driven | Event-driven architecture | Google Cloud | Google Cloud Platform | Infrastructure as Code | Kafka | LLMs | Lakehouse | Medallion Architecture | Microsoft Azure | Python | RAG | RBAC | SQL | Snowflake | Streaming Data | Terraform | Vector Databases | Web Services | “as-code”
Education
N/A
Roles
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