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Data Engineering & Analytics

Build scalable data pipelines, real-time analytics, and business intelligence that turns raw data into competitive advantage.

What We Deliver

Data That Powers Decisions

From ETL pipelines to real-time streaming, from data warehouses to interactive dashboards — we build the data infrastructure that lets you understand your business and predict the future.

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ETL Pipelines

Extract, transform, load. Automate data ingestion from any source. Clean, validate, enrich. Deliver trusted data daily.

Real-Time Streaming

Kafka, Kinesis, Pub/Sub. Process data as it arrives. Millisecond latency. React to events instantly.

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Data Warehouses

Snowflake, BigQuery, Redshift. Structured, queryable, scalable. Your single source of truth.

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Business Intelligence

Tableau, Looker, Power BI. Interactive dashboards. Real-time KPIs. Self-service analytics for your team.

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Data Governance

Data quality, lineage, metadata. Compliance and discoverability. Know where every number comes from.

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Performance Optimization

Query optimization, indexing, partitioning. Fast queries even on terabytes of data. Save on cloud costs.

Core Capabilities

Modern Data Stack

dbt for transformations, Apache Airflow for orchestration, modern cloud data warehouses. Best-in-class tooling.

Data Integration

Fivetran, Stitch, custom connectors. Connect any source to your warehouse. APIs, databases, SaaS, files.

Stream Processing

Kafka, Spark Streaming, Flink. Real-time aggregations, windowing, event-driven processing.

Analytics & BI

Dashboard design, data visualization, user training. Make insights accessible to entire organization.

Data Modeling

Dimensional modeling, star schemas, slowly changing dimensions. Logical, efficient, performant structures.

Analytics Engineering

dbt models, data tests, documentation. Treat data transformations like code. Version control, CI/CD.

Technologies We Use

BigQuery Snowflake Redshift Apache Spark dbt Apache Airflow Kafka Tableau Looker Python
Our Process

Data Architecture Framework

1

Assessment

Understand current data landscape. Identify sources, pain points, growth opportunities.

2

Design

Architecture modern data warehouse. Plan integrations, transformations, governance model.

3

Implementation

Build pipelines, load data, transform, test. Deploy with zero downtime.

4

Analytics & Training

Create dashboards, enable self-service, train teams. Continuous improvement.

Case Study: Axelion Data Warehouse

Challenge: E-commerce company had data scattered across Salesforce, Shopify, Google Analytics, internal databases. No unified view. Dashboards took weeks to create.

Solution: Built modern data warehouse on BigQuery. Automated ETL pipelines via Airflow. Created dbt transformations. Built Looker dashboards for real-time insights.

Result: 10x faster reporting, 30% faster insights, 95% cost reduction vs. previous solutions. Sales team now self-serves analytics daily.

10x
Faster Reports
95%
Cost Savings
2mo
Time to Live
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Build Your Data Foundation

Data warehouse projects range from $75k (MVP) to $250k+ (enterprise). We charge per milestone with clear deliverables.