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Data Platforms Built for Reliability at Scale

DTG designs the pipelines, warehouses, and lakehouses that make your data available, consistent, secure, and ready for analytics and AI.

  • ETL / ELT Pipelines
  • Lakehouses
  • Streaming
  • Data Quality
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Overview

The Foundation for Analytics and AI

Dashboards and AI models are only as good as the data behind them. When pipelines break silently, sources disagree, and nobody knows where a number came from, every downstream initiative slows down.

DTG engineers data platforms that treat data as a product: ingested reliably, modelled consistently, tested automatically, observable end to end, and secured according to your governance requirements.

What you get with DTG

  • Automated batch and streaming pipelines with clear ownership
  • Modern warehouse or lakehouse architecture sized to your needs
  • Data quality tests, lineage, and observability built in
  • Security, access control, and governance by design

Core Services

What We Deliver in Data Engineering

End-to-end capabilities, from strategy and architecture through build, launch, and ongoing improvement.

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Data Lakes, Lakehouses & Warehouses

Architecture and build of cloud storage and compute layers that fit your workloads, budget, and existing platforms.

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ETL / ELT Pipeline Design

Automated, version-controlled pipelines that ingest, transform, and load data on a dependable schedule.

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Batch & Streaming Processing

Scheduled batch jobs alongside event-driven streaming with Kafka for use cases that need fresher data.

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Data Modeling & Warehouse Modernization

Dimensional and domain models, plus migration paths from legacy warehouses to modern cloud platforms.

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Data Quality & Testing

Automated tests for freshness, completeness, and validity so issues are caught before they reach users.

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Observability & Lineage

End-to-end lineage and pipeline monitoring that show where data came from and what changed.

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API & System Integration

Reliable connectors to SaaS applications, operational databases, files, and internal APIs.

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Data Security & Governance

Encryption, fine-grained access control, masking, and cataloging aligned with your policies.

Technology Stack

Tools We Work With

We are technology-pragmatic: we recommend tools that fit your existing ecosystem, skills, and budget.

Cloud Data Platforms

We are platform-pragmatic and recommend what fits your workloads and existing investments.

  • Snowflake

    Cloud data warehouse with separated storage and compute.

  • Databricks

    Lakehouse platform for data engineering, analytics, and ML.

  • Google BigQuery

    Serverless warehouse with built-in scalability.

  • Delta Lake / Apache Iceberg

    Open table formats for reliable lakehouse storage.

Business Benefits

Why It Matters

Data Engineering is ultimately about business outcomes. These are the results we design every engagement around.

Outcomes depend on each organization's starting point, data, and scope. We agree on success measures together during discovery.

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Reliable Data Delivery

Pipelines run on schedule, recover from failure, and alert the right people when something needs attention.

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Consistent, Trusted Data

Shared models and automated tests mean every team works from the same, validated data.

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Scalable Foundations

Architecture that grows with data volume and new use cases without constant re-engineering.

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Ready for Analytics & AI

Clean, well-documented data shortens the path from idea to dashboard or model.

Industry Use Cases

How This Could Work for You

Illustrative scenarios showing how DTG would approach common challenges. These are examples, not descriptions of specific client engagements.

E-CommerceIllustrative example

Unified Customer & Order Data Platform

How an online retailer could unify fragmented order, product, and behavioral data.

#E-Commerce#Lakehouse#Kafka
LogisticsIllustrative example

Real-Time Shipment Tracking Pipeline

How a logistics provider could move from overnight batches to event-driven visibility.

#Logistics#Streaming#Airflow
EnterpriseIllustrative example

Legacy Warehouse Modernization

How an enterprise could migrate an on-premise warehouse to a cloud platform with minimal disruption.

#Modernization#Migration#dbt
AI ReadinessIllustrative example

Feature-Ready Data for Machine Learning

How a product team could prepare reliable, governed data for its first ML models.

#AI/ML#DataQuality#Governance

How We Deliver

The DTG Delivery Methodology

A consistent, four-stage approach we apply across every engagement, tailored to the specifics of each service.

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1. Discovery & Assessment

Map your data landscape, pain points, and the outcomes the platform must support.

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2. Architecture & Prototyping

Design the target architecture and prove it with a thin, end-to-end slice.

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3. Implementation & Integration

Build production pipelines, models, and integrations with testing and monitoring.

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4. Optimization & Continuous Improvement

Tune cost and performance, onboard new sources, and mature data operations.

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Build a Data Platform Your Teams Can Rely On

Talk to DTG about your data sources, pain points, and goals. We will help you design a practical path to a reliable platform.

Schedule a Consultation