Sold by: Modus Create
Fragmented data architectures and manual data pipelines increase operational risks and delay analytics and artificial intelligence initiatives. This data lakehouse implementation establishes a governed, scalable foundation on AWS using reusable medallion engineering patterns, automated data quality controls, and robust pipeline observability. Organizations achieve production-ready data pipelines with built-in security, automated governance, and a validated roadmap for enterprise scale.
Overview
Build a governed, scalable, and AI-ready data lakehouse medallion foundation on AWS.
Fragmented enterprise data, inconsistent governance controls, and ad-hoc ingestion pipelines create delivery friction and delay analytics initiatives. As organizations scale their data products, artificial intelligence models, and agentic workloads, maintaining security, lineage, and pipeline reliability across disparate architectures becomes increasingly complex.
This implementation accelerator establishes a governed lakehouse foundation on AWS native using AWS Lake Formation, AWS Glue, Amazon S3, and Amazon Redshift, alongside supported partner platforms like Databricks on AWS and Snowflake on AWS. The engagement deploys reusable medallion engineering patterns (Bronze, Silver, and Gold layers), automated data contracts, CI/CD deployment pipelines, and continuous observability to turn raw data into validated, business-ready assets.
Key activities
- Architecture and governance setup: Establish environment architecture, CI/CD deployment pipelines, catalog registration, lineage tracking, and sensitive-data access controls.
- Priority data ingestion: Adapt reusable ingestion patterns to priority data sources and implement raw Bronze-layer data capture with integrated data contracts and quality validation.
- Transformation and pipeline validation: Implement Silver and Gold layer transformations to curate business-ready data outputs, conduct end-to-end testing, and configure pipeline monitoring.
- Handoff and roadmap delivery: Complete operational handoff, deliver system documentation, conduct team enablement, and finalize a production scale roadmap.
Deliverables:
- Governed platform foundation including environment architecture, catalog setup, lineage tracking, and access controls.
- Reusable engineering assets including Bronze, Silver, and Gold ingestion patterns, data contracts, automated test suites, and CI/CD templates.
- Validated representative pipelines featuring priority-source ingestion, curated transformations, and end-to-end test results.
- Operational readiness package containing pipeline monitoring configurations, automated quality checks, and operating documentation.
- Knowledge transfer package including team enablement sessions, implementation findings, and a production scaling roadmap.
Highlights
- Establish a governed data lakehouse architecture with automated cataloging, policy enforcement, and sensitive-data handling on AWS.
- Deploy reusable medallion ingestion and transformation patterns with automated data contracts and quality testing.
- Implement end-to-end pipeline observability and CI/CD integration to ensure continuous delivery and operational reliability.
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