“After researching and qualifying several software development service options for the development of a cross-platform application, we fortunately selected Simform as our partner. This turned out to be a very good decision overall, as their performance has been outstanding. The complete engagement from the Simform staff is remarkable. Their team diligently assesses and executes in a very competent manner.”
Databricks
Turn scattered data into governed analytics and AI on Databricks
Most Databricks estates add pipelines, dashboards, and models faster than the access rules, quality checks, and cost controls needed to run them. Simform, a Bronze tier Databricks partner, designs and builds the architecture, data pipelines, and Unity Catalog governance that keeps every workload reliable and its spend traceable to an owner.
I'd Like To Know More!
Databricks engineering for every stage of the platform lifecycle
Simform brings Databricks expertise across the full platform lifecycle, from the initial estate assessment through migration, pipeline engineering, governance, performance tuning, and ongoing operations. We help enterprises build each stage around the workloads the business is waiting on, rather than stopping once a workspace is up and running.
Lakehouse Migration and Platform Modernization
Move legacy warehouses, Hadoop clusters, and ETL estates to Databricks and leave their cost and performance limits behind. A like-for-like conversion reproduces years of workarounds on a platform that was chosen to remove them.
We inventory the existing estate, design the target lakehouse, and migrate in waves, rewriting transformation logic where conversion alone would preserve old flaws. Each workload is reconciled against the legacy system before cutover, so reports and downstream integrations keep working throughout.
Data Engineering and Integration
Give analytics and AI teams data that arrives complete, on schedule, and already validated. Most data incidents start upstream, in a pipeline that failed without an alert or loaded a partial file.
We build ingestion, transformation, and orchestration on Lakeflow, connecting enterprise applications, databases, and files to curated tables through pipelines that are version controlled, tested, and monitored. Quality expectations and recovery behavior are built into every pipeline, so a failed load is caught at the source.
Unity Catalog Governance and Security
Answer who can see which data, where it came from, and who changed it, for every table, model, and dashboard on the platform. Governance added after teams have built their own workspaces means reworking permissions one workspace at a time.
We implement Unity Catalog as the single governance layer, structuring catalogs, ownership, and access policies around the way your business is organized. Lineage, auditing, and classification are in place from the first workload, so compliance evidence builds up through normal work.
Real-Time and Streaming Analytics
Respond to a stock-out, a suspicious payment, or a failing sensor in seconds, while a response can still change the outcome. Streaming earns its cost only where a faster answer leads to a different decision.
We build streaming pipelines on Databricks that land events in the same Unity Catalog table your batch data uses, so real-time and historical views agree. Each stream gets a latency target set by the decision it feeds, which reserves always-on compute for the cases that need it.
BI and Analytics on Databricks SQL
Give business teams answers they can act on without waiting on an analyst or questioning the number. Trust in a dashboard breaks the first time two reports show different figures for the same metric.
We build the serving layer on Databricks SQL warehouses, with metric definitions agreed once and reused behind every dashboard and every question asked in plain language. Existing BI tools such as Power BI and Tableau connect to the same layer, so every team reads the same figure.
AI and Machine Learning on Databricks
Put models and AI agents into production on the data your business already trusts for reporting. Databricks reports that companies using AI governance get over 12 times more AI projects into production.
We build, evaluate, and deploy models and agents on Databricks, with experiment tracking, evaluation before release, and serving sized to real traffic. Permissions, evaluation, and monitoring ship with the first release, so each model can be audited from the day it goes live.
Certified Databricks expertise backed by engineering depth across your whole data estate
Simform pairs a certified Databricks team with engineering breadth across cloud, data, and applications, so each platform decision fits the systems around it and holds up once your own teams take over.
Multi-platform architecture
We integrate Databricks with Snowflake, Microsoft Fabric, cloud services, operational systems, and the BI tools already in use, with Snowflake Select Tier and Fabric Featured Partner status behind that work, so each workload runs on the platform that suits it.
Databricks Bronze Tier Partner
Simform is a Bronze tier partner in the Databricks Brickbuilder Partner Network, with 50+ Databricks-certified professionals and 100+ badges across the engineers, Delivery Experts, and Project Experts who lead client engagements.
Co-engineering delivery model
Our co-engineering model puts your data and platform teams in every architecture decision, so the Databricks platform you take over is one your engineers helped design and can extend on their own.
Databricks engineering at scale
200+ data engineers within a 1,200+ engineer organization bring depth across ingestion, transformation, streaming, governance, and analytics engineering, built over 12+ years of delivering data platforms for enterprises.
AI engineering on governed data
Experience building machine learning models, retrieval pipelines, and AI agents directly on lakehouse data lets your teams move from analytics to AI without a second platform, or connect Databricks to the wider enterprise AI stack where a workload calls for it.
Production ownership discipline
We hold data projects to product-team standards, with CI/CD, automated testing, observability, and post-launch ownership in every engagement, so the platform keeps performing long after the first workloads go live.
Trusted by the world's leading companies
Sonny Cutwright, Operations Manager
Bon Appetit
“Simform rearchitected and modernized our subscription management & billing platform as part of the multi-phase development initiative. The team quickly understood our business requirements and delivered a modern, modular architecture aligned with our scaling needs. Without disrupting our operational workflows, Simform handled complex data migration with precision and supported our legacy modernization journey with seamless ERP integrations.”
Robel Yemane, Head of Engineering
Privilee
“Simform was an invaluable partner in our system modernization, moving beyond analysis to deliver true product engineering advisory. They analyzed complex legacy workflows into clear, validated, developer-ready user stories. The clarity and strategic consistency they introduced was foundational, directly influencing our cloud architecture and product design. Their work effectively accelerated our discovery phase and time to market.”
Director of Engineering
Datamark
“We partnered with Simform to centralize our preclinical research data. They understood technical data challenges and scientific workflows. They helped us build a platform for data ingestion, OCR-based extraction, standardization, analysis, and visualization. Our researchers can use natural language or a visual query builder to analyze complex datasets, while real-time charts and statistical outputs speed up discovery. We liked the ability of the team at Simform to combine strong data engineering capabilities with practical analytics experience.”
Data and Analytics Manager
Preclinical Research Analytics Platform
“The cloud migration was a great sucess. Very satisfactory, seamless and increased our productivity. The most impressive part about Simform is their dynamic and well-versed team. Anytime there was a concern, we were able to communicate and have it rectified immediately.”
President
Trusted Community Services Organization
“Simform led the discovery phase for our digital infrastructure overhaul, bringing a mix of deep technical expertise and a truly collaborative spirit. They took our complex requirements and turned them into a solid product blueprint and a clear, prioritized roadmap. Everything stayed on track thanks to their structured project management. The level of strategy and architecture they brought to the table gave us the certainty we needed to take the next steps.”
Department Manager
Eye Recommend
“Our overall experience with Simform was very positive. They worked as an end-to-end technology partner and integrated well with our engineering and operations teams. This was not just about building a mobile app; it also required careful thinking around data quality, workflows, and long-term system design. Simform brought a practical, product-minded approach and designed an Azure Data Factory pipeline to clean and organize data before it reached the app and admin dashboard.”
Marketing Manager
Patient-Facing Digital Application & Data Platform
“We’re very satisfied with Simform as our engineering partner. We wanted a platform to support the full lifecycle of our field inventory and ease operations for field reps, hospitals and analysts. They translated our complex requirements into an easy-to-use solution and handled development from UI/UX to backend and DevOps. The app works seamlessly across user groups and has a first-class, consistent and simple interface.”
Brad Spataro, Commercial Operations Manager
Evergen
Case studies
Discover the many ways in which our clients have embraced the benefits of the Simform way of engineering.
Vending operations provider cuts stockouts 30% with unified data platform on Databricks
Read More
AI Training Services Provider Enhances Workforce Operations with Databricks
Read More
Sports Brand Boosts ROI 40% with Customer Data Platform
Read More
Automotive Improves Data Accuracy 80% with Data Platform
Read More
From our experts
Frequently Asked Questions
Databricks runs on AWS, Microsoft Azure, and Google Cloud. We design the lakehouse for the cloud where your data and applications already live, so adopting Databricks doesn’t force a second migration. The governance, pipeline, and cost practices described on this page carry across all three.
Yes. An existing platform that has grown expensive, slow, or hard to govern is a common starting point. We review how workloads are designed, how reliable the pipelines are, how access is controlled, and where compute is being spent, then re-engineer the areas holding the platform back. Where workspaces still sit outside Unity Catalog, bringing them under it is usually the first step.
Databricks bills for the compute each workload consumes, so most of the cost is set by design decisions about pipelines, clusters, and SQL warehouses. We size compute to each workload, tune queries and schedules, and apply tags and budgets from the start. Usage reporting then shows spend by team and use case, which keeps the bill explainable as adoption grows.
It depends on how many source systems are involved, how much transformation logic they carry, and how much of that logic should be redesigned along the way. Every engagement opens with an assessment that produces a sequenced roadmap with milestones specific to your estate. A first wave of workloads moves early, which proves the approach and the timeline before the larger ones follow.
Yes. Most enterprises already run more than one data platform, and Simform is also a Snowflake Select Tier Partner and a Microsoft Fabric Featured Partner. We work out which workloads belong on Databricks, how data moves between it and the platforms already in place, and where one governed copy can serve several tools.
Your team knows the business and its data better than any partner will. The gap is usually capacity and pattern experience: migrating without disrupting reporting, setting up governance that scales, and avoiding design choices that inflate compute costs later. Our co-engineering model keeps your engineers in every architecture decision while we bring certified Databricks specialists and patterns from earlier platform builds.
Let’s talk
Hiren Dhaduk
Creating a tech product roadmap and building scalable apps for your organization.
Call Us Now
