Databricks Consulting & Lakehouse Services
Sphere helps data-driven enterprises design, implement, and operationalize the Databricks Lakehouse Platform — unifying data engineering, analytics, and AI on a single, governed foundation. Multi-cloud delivery on AWS, Azure, and GCP.
Trusted by Leading Enterprises
What's Included in Sphere's Databricks Services
Sphere covers the Databricks Lakehouse end to end: architecture, Unity Catalog, Delta Live Tables, MLflow operationalization, Databricks SQL, and migrations from legacy warehouses.
Lakehouse Architecture & Delta Lake
Design and implement a medallion (Bronze/Silver/Gold) architecture on Delta Lake — with ACID transactions, schema enforcement, time travel, and optimized file compaction for reliable, high-performance data pipelines.
Unity Catalog Data Governance
Implement Databricks Unity Catalog for fine-grained access control, column-level masking, lineage tracking, and data sharing across workspaces — establishing the governance foundation for enterprise AI and analytics.
Delta Live Tables Pipelines
Build reliable, declarative streaming and batch data pipelines with Delta Live Tables — including data quality expectations, pipeline observability, and automatic dependency management.
MLflow & Model Serving
Standardize ML experimentation with MLflow tracking, register and version production models in the Model Registry, and deploy them to Databricks Model Serving endpoints for low-latency real-time inference.
Databricks SQL & BI Integration
Configure Databricks SQL warehouses, optimize query performance with predictive I/O and caching, and integrate with Power BI, Tableau, and Looker for self-service analytics directly on the lakehouse.
Legacy Data Warehouse Migration
Migrate from Teradata, Netezza, Hive, or cloud data warehouses to the Databricks Lakehouse — including SQL translation, workload assessment, and incremental pipeline cutover strategies.
Why Sphere for Databricks.
The Databricks Lakehouse Platform eliminates the traditional trade-off between data warehouses and data lakes — but realizing its full potential requires expertise across Delta Lake architecture, Unity Catalog governance, and MLflow operationalization. Sphere delivers all three.
What makes Sphere the right Databricks implementation partner:
Lakehouse Architecture Depth
Our data engineers design Delta Lake table formats, medallion architectures, and Unity Catalog hierarchy for performance, cost efficiency, and data quality at petabyte scale.
ML Engineering at Scale
We operationalize machine learning with MLflow experiment tracking, model registry, feature stores, and Databricks Model Serving — bridging the gap between data science and production AI.
Multi-Cloud Delivery
Sphere delivers Databricks on AWS, Azure (Azure Databricks), and Google Cloud — allowing you to build a cloud-agnostic lakehouse or extend an existing cloud investment.
Track record across lakehouse migration, MLOps, and streaming engagements.
Query Cost Reduction
National retailer — Teradata → Databricks Lakehouse on Azure, with Unity Catalog-governed medallion architecture and 4x faster analytical response times.
In Production
Insurance carrier — end-to-end MLOps platform on Databricks. MLflow standardization and 12 risk and fraud models on Databricks Model Serving.
Production Analytics
Manufacturing firm — Delta Live Tables streaming pipelines ingesting IoT sensor data from 30 factory floors into a Databricks Silver layer in near-real-time.
The Databricks Stack Behind It
Sphere implements and operates the Databricks Lakehouse capabilities that modern data and AI platforms actually run on.
Lakehouse Storage
Delta Lake, Iceberg, Unity Catalog, Lakehouse Federation
Data Engineering
Delta Live Tables, Workflows, Auto Loader, Structured Streaming, Asset Bundles
Data Warehousing
Databricks SQL, Photon, Materialized Views, Streaming Tables
Generative AI
Mosaic AI, Foundation Model APIs, Vector Search, AI Gateway, Genie
Machine Learning
MLflow, Feature Store, Model Serving, AutoML, Mosaic AI Training
Governance & Security
Unity Catalog, Lineage, Attribute-based Access Control, System Tables
Infrastructure
Terraform Databricks provider, Asset Bundles, dbt, GitHub Actions
Let's scope your Databricks engagement
Running on Databricks?
Here's Where Sphere Fits.
Legacy Warehouse → Lakehouse
Teradata, Netezza, Hive, Redshift, BigQuery, and Synapse migrations to Databricks Lakehouse — SQL translation, workload assessment, incremental pipeline cutover, and Unity Catalog-governed medallion architecture.
Production MLOps with MLflow
End-to-end MLOps platforms — MLflow experiment tracking, Model Registry promotion workflows, Feature Store pipelines, and Databricks Model Serving endpoints for low-latency real-time inference.
Streaming & IoT Analytics
Delta Live Tables streaming pipelines ingesting IoT sensor data, manufacturing telemetry, and clickstream events into governed Silver layers in near-real-time — for production visibility and operational intelligence.
Unity Catalog Governance
Fine-grained access control, column-level masking, lineage tracking, and cross-workspace data sharing — the governance foundation for enterprise AI, analytics, and regulated environments.
Mosaic AI & Foundation Models
Mosaic AI, Foundation Model APIs, Vector Search, and Genie spaces — for production AI features built on governed lakehouse data without leaving the platform.
Databricks SQL & BI Integration
Databricks SQL warehouses with Photon, Predictive I/O, and Materialized Views — integrated with Power BI, Tableau, and Looker for self-service analytics directly on the lakehouse.
Hear from
our clientsHear from our clients
Lee Ebreo
VP of Engineering at Credit Ninja
These things would not have been achievable if we did not build our own in-house system and if we did not partner with Sphere to help us achieve our goals.
Selah Ben-Haim
VP of Engineering at Prominence Advisors
Our experience with Sphere and their team has been and continues to be fantastic. We keep throwing new projects at them, and they keep knocking them out of the park (including the rescue of a project that was previously bungled by another vendor).
Ben Crawford
Senior Product Manager at Enova Financial
I would expect to be delighted. It's been a really positive experience, working with Sphere, and I would expect you to have the same.
Mark Friedgan
CEO at CreditNinja
Sphere consistently prioritizes the needs of their clients, demonstrating both agility and teamwork. As an offshore team, they have been an integral part of our organization and we plan to continue growing with them.
René Pfitzner
Co-Founder at Experify
Sphere provided excellent full-stack development manpower to augment our team and help push our product forward. They are easy to work with, tech-savvy and proactive.
Bruce Burdick
Chief Information Officer at Integra Credit
We've been working with Sphere and its excellent consultants since our founding. I've found that they are true partners in the success of our business.
Jemal Swoboda
CEO at Dabble
The resources and developers that Sphere Software provides are skilled and have the required technical expertise, but more importantly, they have helped us build a culture of excellence within our team.
Arthur Tretyak
Founder and CEO at IntegraCredit
With Sphere, we were able to migrate in half the time it would take to train an additional FTE… and for a fraction of the cost. Our experience with Sphere has been exceptional.
Lee Ebreo
VP of Engineering at Credit Ninja
These things would not have been achievable if we did not build our own in-house system and if we did not partner with Sphere to help us achieve our goals.
Selah Ben-Haim
VP of Engineering at Prominence Advisors
Our experience with Sphere and their team has been and continues to be fantastic. We keep throwing new projects at them, and they keep knocking them out of the park (including the rescue of a project that was previously bungled by another vendor).
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Client Partner