AI-first engineering

AWS Data Platform Services for Enterprise.

Logiciel builds enterprise AWS data platforms for large organisations. Data lakes on S3, warehouses on Redshift, streaming on MSK and Kinesis, governance with Lake Formation, and pipelines that survive change at enterprise scale. We work alongside data, platform and analytics teams to design, build and operate AWS data platforms that business units can build on.

Book an Intro Call Common Questions

5 steps

Enterprise AWS data platform framework

3 models

Engagement models to deliver the work

Why Logiciel

Why Enterprise AWS Data Platforms Stall.

Why Logiciel · 01

Each business unit runs its own informal AWS data stack.

Why Logiciel · 02

Pipelines are owned by individuals, not teams.

Why Logiciel · 03

Lake Formation governance is partial and inconsistent across business units.

Why Logiciel · 04

Storage costs grow faster than analytical value.

Why Logiciel · 05

BI dashboards and ML pipelines compete for Redshift resources.

Why Logiciel · 06

The platform reports problems but nobody actually responds.

What you get

What You Get When You Work With Logiciel on Enterprise AWS Data.

A modern enterprise AWS data architecture with clear separation between storage, processing and consumption.

Pipelines built in code, with tests, observability and lineage.

Lake Formation governance, fine-grained access and audit-ready logs.

Cost reports mapped to business units and product lines.

A platform that supports BI, machine learning and product analytics across business units.

A documented enterprise operating model that data engineers can run.

Technology

Enterprise AWS Data Platform Solutions Built for Scale.

Enterprise Data Lake on S3

What it meansS3-based data lakes with bronze, silver and gold layers, open table formats like Iceberg and Hudi and Lake Formation governance, sized for enterprise scale.

Enterprise Cloud Data Warehouse on Redshift

What it meansRedshift Serverless and provisioned clusters with workload management, materialised views and federated queries.

Enterprise ETL and ELT

What it meansAWS Glue, dbt on Redshift and Athena, Step Functions and Airflow on MWAA for orchestration across business units.

Enterprise Streaming Data on MSK and Kinesis

What it meansReal-time pipelines for events, telemetry and CDC using MSK, Kinesis Data Streams, Kinesis Firehose and Flink on KDA.

Enterprise Data Governance and Cataloguing

What it meansLake Formation, Glue Data Catalog, fine-grained access control, lineage with OpenLineage and audit-ready logging across business units.

Enterprise ML and AI on the Data Platform

What it meansFeature stores on SageMaker, training pipelines, vector stores for RAG and inference workloads tied to governed data.

Enterprise Data Observability and Reliability

What it meansPipeline monitoring, freshness, volume and schema checks, alerting and SLAs across business units.

Engagement

Engagement Models Designed for AWS Data Platform Services for Enterprise Delivery.

Dedicated Enterprise AWS Data Platform Squad

A long-running team of AWS data engineers, platform engineers and analytics specialists embedded in your enterprise data function.

Engagement

Data Platform Advisory and Staff Augmentation

Senior AWS data architects and engineers who reinforce your enterprise team during build phases.

Engagement

Outcome-Based Data Platform Engagements

Fixed-scope work for a specific outcome, for example a Redshift migration, a Lake Formation rollout or a streaming pipeline launch across business units.

Engagement

Under the hood

Enterprise AWS Data Platform Services We Deliver.

Enterprise AWS Data Architecture and Strategy

Reference architectures, maturity assessments and multi-year data platform roadmaps.

Included

Enterprise AWS Data Lake Implementation

S3-based data lakes with Iceberg or Hudi, partitioning, compaction, governance and access patterns.

Included

Enterprise Redshift and Lakehouse Engineering

Redshift Serverless, provisioned clusters, workload tuning, dbt models and federated queries across Redshift and S3.

Included

Enterprise ETL and ELT Pipeline Engineering

Glue, MWAA, Step Functions, dbt and Spark-on-EMR pipelines.

Included

Enterprise Streaming Data Pipelines on AWS

MSK, Kinesis, Flink on KDA, schema registry and exactly-once patterns.

Included

Enterprise AWS Data Governance and Lake Formation

Lake Formation, Glue Data Catalog, IAM Identity Center, row and column-level security, and audit reporting.

Included

Enterprise Data Observability and Reliability Engineering

Freshness, volume and schema monitoring, SLA reporting, incident response and on-call.

Included

Enterprise AI and ML Data Integration on AWS

SageMaker feature stores, RAG architectures, vector stores and integration with Bedrock and SageMaker pipelines.

Included

Technology

AWS Data Platform Services for Enterprise Insights & Frameworks.

Patterns from our delivery teams that have run through real enterprise deployments.

Enterprise AWS Lakehouse Reference Architecture

A practical lakehouse pattern that combines S3, Iceberg, Redshift, dbt and Lake Formation for governed analytics across business units.

↳ Technology

Enterprise AWS Streaming Data Platform Pattern

A production pattern for CDC, event streaming and real-time analytics on MSK, Kinesis and Flink.

↳ Technology

Technology

Our AWS Data Platform Services for Enterprise Framework.

Discovery and Use Case Mapping

We map the business use cases, current data estate, governance constraints and cost expectations across business units.

Target Architecture and Roadmap

We design the AWS data architecture, choose patterns per use case and agree on a phased roadmap.

Platform Build

We build the platform in code, including storage, compute, orchestration, governance and observability.

Use Case Onboarding Across Business Units

We onboard the first BI, analytics and ML use cases with data contracts, SLAs and access patterns.

Operate and Scale

We move into a steady-state operating model and widen the platform across business units and product lines.

Resources

Insights for tech leaders.

Whitepaper · PDF

How a VP of Data Got a Modern Data Platform Funded in Two Board Meetings

Whitepaper · PDF

Building AI-Ready Healthcare Data Infrastructure: The 90-Day Roadmap from Staging Bottleneck to Production

Whitepaper · PDF

How an Energy Company Stopped Paying for Silent Data Quality Failures

Questions

Frequently asked questions.

What does AWS Data Platform Services for Enterprise include?

We cover strategy, architecture, build, deployment and operations for AWS Data Platform Services for Enterprise, aligned with your business priorities and operating constraints.

How long does AWS Data Platform Services for Enterprise typically take?

Most engagements reach a working pilot within 4-8 weeks, while larger rollouts run across phased waves over several months.

Can Logiciel integrate AWS Data Platform Services for Enterprise with our existing systems?

Yes. We integrate with cloud platforms, CRMs, ERPs, EHR, OT systems, analytics tools and other operational infrastructure depending on the use case.

Do you offer fixed-cost engagements for AWS Data Platform Services for Enterprise?

Yes. We offer milestone-based pricing once scope, KPIs and delivery requirements are agreed.

Who owns the deliverables from a AWS Data Platform Services for Enterprise engagement?

You retain ownership of all workflows, integrations, prompts, infrastructure, systems and implementation assets.

How do you handle governance and compliance for AWS Data Platform Services for Enterprise?

We implement governance frameworks, observability, access controls, audit trails and compliance-aligned deployment practices.

How do you optimize cost for AWS Data Platform Services for Enterprise?

We tune infrastructure, automate resource management, optimise deployment workflows and report operational cost back to teams and product lines.

Do you support ongoing operations after launch for AWS Data Platform Services for Enterprise?

Yes. We run managed operations with SRE, observability, on-call and continuous improvement.

Let's build

Accelerate AWS Data Platform Services for Enterprise.

Ready to put AWS Data Platform Services for Enterprise on production-software footing? Partner with Logiciel to design, build and operate AWS Data Platform Services for Enterprise that engineering, security and business teams can all defend.

Design your enterprise AWS data platform

AWS Data Platform Services for Enterprise.

See Logiciel in action.

Why Enterprise AWS Data Platforms Stall.

Each business unit runs its own informal AWS data stack.

Pipelines are owned by individuals, not teams.

Lake Formation governance is partial and inconsistent across business units.

Storage costs grow faster than analytical value.

BI dashboards and ML pipelines compete for Redshift resources.

The platform reports problems but nobody actually responds.

What You Get When You Work With Logiciel on Enterprise AWS Data.

Enterprise AWS Data Platform Solutions Built for Scale.

Enterprise Data Lake on S3

Enterprise Cloud Data Warehouse on Redshift

Enterprise ETL and ELT

Enterprise Streaming Data on MSK and Kinesis

Enterprise Data Governance and Cataloguing

Enterprise ML and AI on the Data Platform

Enterprise Data Observability and Reliability

Engagement Models Designed for AWS Data Platform Services for Enterprise Delivery.

Dedicated Enterprise AWS Data Platform Squad

Data Platform Advisory and Staff Augmentation

Outcome-Based Data Platform Engagements

Enterprise AWS Data Platform Services We Deliver.

Enterprise AWS Data Architecture and Strategy

Enterprise AWS Data Lake Implementation

Enterprise Redshift and Lakehouse Engineering

Enterprise ETL and ELT Pipeline Engineering

Enterprise Streaming Data Pipelines on AWS

Enterprise AWS Data Governance and Lake Formation

Enterprise Data Observability and Reliability Engineering

Enterprise AI and ML Data Integration on AWS

AWS Data Platform Services for Enterprise Insights & Frameworks.

Enterprise AWS Lakehouse Reference Architecture

Enterprise AWS Streaming Data Platform Pattern

Our AWS Data Platform Services for Enterprise Framework.

Discovery and Use Case Mapping

Target Architecture and Roadmap

Platform Build

Use Case Onboarding Across Business Units

Operate and Scale

Insights for tech leaders.

How a VP of Data Got a Modern Data Platform Funded in Two Board Meetings

Building AI-Ready Healthcare Data Infrastructure: The 90-Day Roadmap from Staging Bottleneck to Production

How an Energy Company Stopped Paying for Silent Data Quality Failures

Frequently asked questions.

Accelerate AWS Data Platform Services for Enterprise.