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Modern Data Infrastructure

Data Platform Engineering

Production data platforms spanning ingestion, modeling, orchestration, observability, and executive reporting without the usual warehouse chaos.

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Data Platform Engineering

  • Cloud data warehouse: Snowflake, BigQuery, Redshift

  • Medallion architecture (Bronze/Silver/Gold) for data quality

  • Real-time and batch pipelines: Airflow, Spark, dbt

What You Get

Production-grade data infrastructure from warehouse to dashboard

#1

Cloud Data Warehouse

Snowflake, BigQuery, or Redshift — architected for your query patterns, cost profile, and compliance requirements.

#2

Medallion Architecture

Bronze/Silver/Gold layering that enforces data quality progressively, so analysts never query raw ingestion tables.

#3

Pipeline Orchestration

Real-time and batch pipelines with Airflow, Spark, and dbt — tested, monitored, and recoverable on failure.

#4

Analytics & Reporting

Metabase, Looker, or custom dashboards that give executives the operating view they need without waiting on engineering.

#5

Governance & Quality

Data lineage, quality monitoring, and access controls that satisfy compliance audits and build trust in the numbers.

#6

Cloud Migration

From on-prem to AWS, GCP, or Azure with validated migration runbooks, parallel testing, and zero-downtime cutover plans.

How We Engineer Data Pipelines

Medallion architecture from raw ingestion to executive dashboards

App Stores
Ad Networks
Payment APIs
Attribution

Bronze Layer — Raw Ingestion

1B+ records

Every record lands unmodified from all connected sources. Full audit trail, schema-on-read, and automated scheduling ensure nothing is lost.

Silver Layer — Clean & Validate

99.4% accuracy

Deduplication, schema enforcement, currency normalization, and cross-source reconciliation. Data quality gates ensure 99.4% accuracy.

Gold Layer — Analytics-Ready

Real-time

Business-ready aggregations optimized for sub-second dashboard queries. Revenue trends, cohort ROAS, campaign metrics, and P&L rollups.

Executive Dashboards
API Endpoints
Automated Alerts

Data Platform Capabilities

End-to-end data engineering from ingestion to insight

Data Warehousing

SnowflakeBigQueryRedshiftMedallion Architecture

Pipeline Engineering

Airflow & dbtSpark & FlinkReal-time StreamingBatch & ELT Pipelines

Analytics & BI

Metabase & LookerCustom DashboardsData Quality MonitoringSelf-service Analytics

Cloud Migration

AWS, GCP, AzureOn-prem to CloudInfrastructure as CodeCost Optimization

Frequently Asked Questions

A modern data platform centralizes your data in a cloud warehouse with automated pipelines, quality checks, and analytics layers. It replaces siloed databases and manual reporting with a single source of truth that scales.
An MVP data platform typically takes 4-8 weeks: data source inventory, pipeline design, warehouse setup, and initial dashboards. We deliver incrementally - you see results from week 2.
We've built platforms processing 1B+ records across 12 data sources with 34 automated pipelines. Our architectures are designed for 10x growth without re-platforming.
Yes. We migrate on-premise data systems to AWS, GCP, or Azure with zero data loss. This includes warehouse migration, pipeline modernization, and infrastructure-as-code setup for repeatable deployments.
Data governance is built in from day one: data lineage tracking, quality monitoring, access controls, and compliance with GDPR/CCPA. We don't bolt governance on after the fact.

Advisory Mandate

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