Data engineering forms the backbone of any successful data initiative. At Strategic Technology Partners, we build reliable, maintainable data pipelines that transform raw information into actionable insights while empowering your team with modern engineering practices and frameworks.
Our Technical Approach
Our data engineering practice is built on several key technical principles:
Software Engineering Discipline
We bring software engineering best practices to data work, including:
- Version control for all code and configurations
- Comprehensive testing at multiple levels
- Continuous integration and deployment
- Clear documentation and code standards
Declarative Data Transformation
We leverage tools like dbt to implement declarative, version-controlled data transformations that are:
- Self-documenting through clear SQL and robust documentation
- Testable with automated data quality checks
- Modular with reusable components
- Traceable with built-in lineage tracking
Modern Data Stack Integration
We integrate best-of-breed tools into cohesive architectures, including:
- Cloud data platforms (Snowflake, BigQuery, Redshift)
- Databricks for unified analytics
- Streaming technologies for real-time processing
- Orchestration tools for reliable workflow management
Key Services
Pipeline Development and Optimization
We design and implement data pipelines that handle everything from simple batch processing to complex real-time streaming workloads. Our focus on performance optimization ensures your pipelines run efficiently while maintaining reliability.
dbt Implementation and Training
As specialists in dbt (data build tool), we help organizations implement this powerful framework for transforming data in the warehouse. We provide comprehensive training to ensure your team can leverage dbt’s full capabilities.
Data Quality and Testing
We implement robust data quality frameworks that catch issues before they impact downstream systems. Our testing strategies include schema validation, data freshness checks, and custom business rule validation.
Infrastructure as Code
We manage data infrastructure using Infrastructure as Code principles, ensuring environments are reproducible, version-controlled, and easily deployable across different stages of your development lifecycle.
The Collaborative Difference
Unlike traditional data engineering consultants, we focus on building your team’s capabilities:
- Pair Programming: We work directly with your engineers, sharing knowledge in real-time
- Framework Implementation: We establish reusable patterns your team can apply independently
- Documentation and Training: We create comprehensive guides and conduct training sessions
- Gradual Handover: We ensure smooth knowledge transfer throughout the engagement
