Backend Data Platform Engineer

Position Overview
This role specializes in backend systems for data analytics platforms, focusing on data pipeline architecture, processing infrastructure, and analytics API development. The position requires strong engineering fundamentals applied to data-intensive applications.

Primary Responsibilities

Data Pipeline Development

• Design and implement ETL/ELT processes for analytical data
• Develop data ingestion systems from multiple source platforms
• Build transformation logic for data normalization and enrichment
• Implement data validation and quality assurance mechanisms

Processing Infrastructure

• Develop batch and streaming data processing systems
• Optimize data workflows for performance and reliability
• Implement monitoring and alerting for data pipeline operations
• Design fault-tolerant data processing architectures

Analytics API Development

• Build RESTful APIs for data access and analytical queries
• Develop data aggregation and calculation endpoints
• Implement authentication and authorization for data services
• Optimize API performance for complex data operations

Database & Storage Engineering

• Design and optimize analytical database schemas
• Implement data partitioning and indexing strategies
• Develop data archival and lifecycle management systems
• Optimize storage solutions for analytical workloads

Technical Requirements

Core Programming

• Python (Pandas/NumPy) for data processing applications
• SQL proficiency for complex analytical queries
• Experience with data pipeline frameworks and tools

Data Systems

• Database optimization for analytical workloads
• Data warehousing concepts and implementations
• Experience with big data processing technologies

Infrastructure

• Cloud platform experience (AWS/GCP/Azure)
• Containerization and orchestration understanding
• CI/CD practices for data applications

Development Methodologies

• Test-driven development for data quality assurance
• Version control and collaborative development practices
• Documentation standards for data systems and APIs
• Performance benchmarking and optimization approaches

Work Output Expectations

• Reliable data pipeline implementations
• Scalable analytical API services
• Comprehensive system documentation
• Performance optimization contributions

This position requires analytical thinking, systematic approach to data problems, and engineering rigor in building reliable data infrastructure.