Data Engineering

Data Warehouse
& Lakehouses

Scalable Cloud Analytics. Petabyte Spatial Pipelines.

Transform massive tabular, telemetry, and spatial datasets into actionable business intelligence. We design modern cloud data warehouses and geospatial lakehouses leveraging Snowflake, Google BigQuery, Amazon Redshift, and dbt to deliver real-time analytics at scale.

View Services
spatial_analytics.sql • dbt_model.sql BigQuery & Snowflake
Cloud Data Warehouse and Spatial Analytics Architecture
WITH regional_metrics AS (
  SELECT region_id, COUNT(*) AS total_events,
  ST_UNION_AGG(event_geom) AS coverage_area
  FROM `dw.telemetry_partitioned`
  GROUP BY region_id
) SELECT * FROM regional_metrics;
Petabyte-Scale Engine dbt & Spatial Analytics
Cloud Native
Snowflake & Redshift
Google BigQuery
Petabyte Scale

Decoupled compute and columnar storage querying billions of rows in seconds.

Native Geospatial SQL

BigQuery GIS and Snowflake Geography data types executing spatial joins.

Modern ELT & dbt

Version-controlled data transformations with automated quality test suites.

Lakehouse Unification

Unifying raw IoT telemetry, historical logs, and GIS layers in one platform.

Our Services

Our Data Warehouse Services

We architect and implement scalable data warehouse solutions that consolidate siloed enterprise data, automate ETL workflows, and enable lightning-fast spatial analytics.

Cloud Warehouse Architecture

Designing resilient Snowflake, BigQuery, and Redshift architectures tailored for heavy concurrent analytical queries.

Geospatial Lakehouses

Ingesting satellite imagery metadata, LiDAR telemetry, and OpenStreetMap data into high-performance lakehouse schemas.

Automated ELT / ETL Pipelines

Building fault-tolerant Apache Airflow DAGs, Kafka streams, and dbt models with incremental ingestion models.

Dimensional Modeling

Constructing Star and Snowflake dimensional models optimized for BI dashboards, Tableau, and geospatial map visualization.

Cost & Query Optimization

Partitioning, clustering keys, materialized views, and compute autoscaling to eliminate unnecessary cloud spending.

Data Governance & Quality

Data contract enforcement, Great Expectations test suites, role-based access control, and metadata lineage catalogs.

Our Process

How We Work

An engineering pipeline that transforms fragmented data silos into trusted, high-performance analytical assets.

01

Discovery

Audit source systems, IoT streams, GIS layers, and reporting SLAs.

02

Architecture

Storage tiering, clustering keys, security models, and warehouse sizing.

03

Pipelines

Building robust dbt transformation models, Airflow DAGs, and validation tests.

04

Validation

Data reconciliation, latency benchmarking, and query cost profiling.

05

BI Launch

Connecting BI dashboards, GIS web apps, and automated alerts.

Technologies We Use

Our Tech Stack

We build with premier cloud analytics platforms and modern data stack (MDS) orchestration tools.

Cloud Warehouse Platforms

Snowflake, Google BigQuery GIS, Amazon Redshift & Databricks

ELT & Orchestration

dbt Core, Apache Airflow, Apache Kafka, DuckDB & Apache Iceberg

Ready to Build Your Scalable Modern Data Warehouse?

Partner directly with our Senior Data Architects. We streamline your data ingestion, build high-speed spatial analytics, and empower your organization with trusted intelligence.