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Data Engineering - Infrastructure Services | Borealis Insight
Infrastructure

Data
Engineering.

The foundation of intelligence. We design, build, and maintain the high-performance data pipelines that feed your analytics and AI agents.

Building Intelligence Infrastructure

Modern enterprises generate massive volumes of data every second. But raw data alone creates no value. The competitive advantage comes from transforming that data into reliable, accessible intelligence that powers decision-making across your organization.

Our data engineering practice focuses on building robust, scalable infrastructure that handles the complete data lifecycle. We architect systems that ingest data from diverse sources, transform it for analytical use cases, and deliver it to your business intelligence tools with enterprise-grade reliability.

Pipeline Architecture
Cloud Data Warehouse
Real-time Streaming
Data Quality Frameworks
API Development
Performance Tuning

ETL & ELT Pipeline Development

Data integration is the backbone of modern analytics. We build custom connectors and transformation workflows that move data reliably from source systems to your analytical environments.

Custom Connectors

Python-based integrations for APIs, databases, SaaS platforms. We handle authentication, rate limiting, and pagination automatically.

Transformation Logic

dbt models that implement business rules and data quality checks. Version-controlled SQL that your team can maintain.

Orchestration

Airflow DAGs with robust error handling, automatic retries, and alerting. Ensure pipelines run on schedule.

Data Warehouse Architecture

Your data warehouse is the analytical foundation of your organization. We design and optimize architectures on Snowflake, BigQuery, and Redshift that balance performance, cost, and usability. Our approach focuses on dimensional modeling techniques that make data intuitive for analysts.

  • Warehouse Optimization

    Partitioning, clustering, and materialized views.

  • Dimensional Modeling

    Star and Snowflake schemas for business clarity.

  • Cost Management

    Resource monitors and efficient query design.

FACT
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Data Quality & Governance

Bad data leads to bad decisions. We implement automated testing frameworks (Great Expectations) that catch issues before they impact your business.

  • Schema Validation
  • Completeness Checks
  • Duplicate Detection

API Development

Your processed data needs to reach applications securely. We build RESTful and GraphQL endpoints that serve analytical data with proper authentication.

  • OAuth 2.0 Security
  • Rate Limiting & Caching
  • OpenAPI Documentation

Technology Stack Excellence

Python SQL Apache Airflow dbt Snowflake BigQuery Redshift AWS Azure Docker Kubernetes

Our Data Engineering Process

01

Discovery

Assess architecture & pain points.

02

Design

Create scalable solution blueprints.

03

Develop

Agile sprints with CI/CD.

04

Deploy

Controlled production rollout.

05

Optimize

Ongoing tuning & support.

Proven Results

3x
Faster Query Performance
40%
Cost Reduction
99.9%
Pipeline Reliability

Ready to Build Your Data Foundation?

Modern data engineering requires specialized expertise. Whether you're building your first warehouse or modernizing legacy pipelines, we provide the capability you need.