AI, Data & Intelligence
Data Lakehouse Architecture
Building modern data lakehouses using Databricks Delta Lake, Apache Iceberg and Snowflake for real-time analytics and AI.
Capability overview
What data lakehouse architecture involves
Data lakehouse architecture unifies the low-cost scalability of data lakes with the ACID transaction reliability and high performance of data warehouses. We build enterprise data lakehouses using Databricks Delta Lake, Apache Iceberg and Snowflake.
We enable real-time streaming ingestion, ACID transaction isolation, time-travel data versioning and high-speed SQL analytics over open storage formats.
Our lakehouse architectures power both BI reporting dashboards and machine learning workloads from a single, unified storage foundation.
Our methodology for data lakehouse architecture combines disciplined technical execution with proactive risk management from initial lakehouse architecture blueprint through to final production rollout. We configure automated alerting, role-based access permissions and detailed operational runbooks for databricks & delta lake setup so your team retains total operational confidence.
We provide dedicated engineering oversight, automated telemetry tracking and structured technical handovers for databricks & delta lake setup and apache iceberg implementation, ensuring long-term operational resilience.
What is included
What the engagement covers
Databricks & Delta Lake Setup
Architecting Delta Lake lakehouses with Medallion Architecture (Bronze, Silver, Gold data layers).
Apache Iceberg Implementation
Building open table format data lakehouses using Apache Iceberg for multi-engine query support.
ACID & Time-Travel Data Management
Configuring ACID transaction guarantees, schema enforcement and historical time-travel query features.
Unified BI & AI Data Access
Connecting SQL BI engines (Power BI, Tableau) and ML frameworks (PyTorch, Spark ML) to the single lakehouse storage layer.
How we work
How we deliver data lakehouse architecture
Lakehouse Architecture Blueprint
Designing Medallion data layer structures, table storage formats, compute clusters and governance rules.
Storage Layer Implementation
Configuring Delta Lake or Iceberg tables over AWS S3, Azure Data Lake or GCP Cloud Storage.
Medallion Pipeline Engineering
Building PySpark and Delta Live Tables (DLT) pipelines transforming raw Bronze data to Silver and Gold layers.
Query Engine Tuning
Optimizing Databricks SQL warehouses, Photon query acceleration, Z-Ordering and liquid clustering.
Security & Governance Integration
Configuring Unity Catalog or Apache Ranger for centralized fine-grained access control across all data assets.
Related capabilities
Related capabilities in Data Engineering & Platforms
Data Integration
Connecting disparate enterprise applications, databases, SaaS platforms and cloud systems into unified data pipelines.
Real-Time Data Processing
Engineering low-latency streaming data pipelines, event processing engines and real-time analytical dashboards.
Data Migration
Legacy data migration services, cloud database migration, database schema translation and zero-downtime data cutover.
Data Quality Management
Automated data quality profiling, data cleansing pipelines, data validation rules and anomaly monitoring for enterprise data.
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Questions & answers
Questions about Data Lakehouse Architecture
Cannot find what you need? Our team responds to technical and commercial questions within one business day.
Ask a questionMedallion Architecture structures data into Bronze (raw ingestion), Silver (cleansed/conformed) and Gold (business-ready aggregated) layers.
Lakehouse implementation is delivered as a fixed-fee project or through dedicated cloud data engineering squad retainers.
Time Travel allows querying historical table snapshots at any specific past point in time, simplifying audits, rollbacks and historical reporting.
Next step
Discuss data lakehouse architecture with Acmez
Share what you need to change, build, integrate or support. We will map the practical next step.