Enlight Lab
Snowflake · Databricks · Data Warehouse · dbt

Your Data Platform Is Broken. We Fix It.

Snowflake and Databricks implementations that actually work — pipelines that stay running, clean analytics your team trusts, and a data platform built for your volume, not a demo.

Start Free Scoping Call
  • Snowflake and Databricks specialists with production experience at real data volumes.
  • Every dbt model documented, version-controlled, and handed over to your team at completion.
  • Pipelines built with monitoring, alerting, and automated recovery — not silent failures.

Clients include

Emblazer.aiHumaMozilla Foundation

Track Record

22+ MVPs Shipped100% On-Time

Clutch Review

4.8 on Clutch · Jay Joshi, Exar North

“Delivered a working MVP faster than we thought possible.”

Fill in your details below to get started

Start With a Free Scoping Call

Tell us about your project. We respond same business day.

Your enquiry is confidential · NDA on Day 1 · We respond same business day

Or speak with a senior engineer directly:
8 WeeksFrom first scope call to a working product for Emblazer.ai
38%Faster support resolution for Alida, after deploying a custom AI agent
28%Lower cloud and infrastructure cost for Huma, from right-sized architecture
*Representative results from recent engagements. Your numbers will vary.
What You Get

Everything Included. No Hidden Extras.

One engagement, full-stack execution. We own the outcome, not just the deliverables.

01

Snowflake Implementation

Snowflake setup from scratch: schema design, data modelling, cost optimisation, and a transformation layer your analysts can actually use. Built for your data volume, not a generic template.

Fixed-price contractWeekly milestonesLaunch plan
02

Databricks Platform Development

Databricks notebooks, Delta Lake architecture, and Spark pipelines that actually run in production. We build the platform, not just the demo environment.

Technology selection docArchitecture diagramCode documentation
03

dbt Transformation Layer

dbt models that transform raw data into clean, documented, version-controlled datasets. Your analysts write SQL against trusted tables, not raw exports with unknown origins.

Testing suiteProduction deploymentIP transfer
04

Reliable Data Pipelines

Pipeline development with monitoring, alerting, and automated recovery. No more silent failures at 3am or stale dashboards your team cannot trust.

Demo environmentInvestor deck supportLive data integration

Sometimes we'll tell you not to build.

If AI isn't the right answer for your problem, or an off-the-shelf tool would do the job better and cheaper, we'll say so on the call.

Why Enlight Lab

Specific Commitments. Not Marketing Language.

Every firm claims to be reliable, fast, and senior. Here is what those words actually mean in practice when you engage with us.

Snowflake and Databricks Specialists.

We have production experience with Snowflake and Databricks at real data volumes, not just demo environments. We know the difference between a platform that works in a POC and one that works under real load.

Data You Can Actually Trust.

Most data engineering projects fail to deliver because nobody validates the output. We reconcile every pipeline against source systems and hand off only when the numbers actually match.

dbt Native from Day One.

Every transformation we build uses dbt with full documentation, testing, and version control. Your analysts inherit a clean, navigable data model, not undocumented SQL scripts nobody can read.

We Work With Your Existing Team.

Data engineers are expensive and hard to hire. We work alongside your existing team, train them on the systems we build, and leave your team capable of operating independently when the engagement ends.

Snowflake Cost Optimisation Included.

Snowflake bills keep rising faster than your data usage. We audit compute spend, eliminate redundant model runs, implement clustering and partition strategies, and set up cost monitoring from day one.

You Own the Platform.

All pipelines, dbt models, and infrastructure are transferred to your team at completion. We do not build proprietary data platforms or create dependencies that require us to maintain.

Dhananjay Goel, Founder & CEO, Enlight Lab

Dhananjay Goel

Founder & CEO, Enlight Lab

View LinkedIn

I started Enlight Lab because too many founders get sold senior engineers and handed juniors after they sign. That does not happen here.

I stay involved in every engagement, from the first scope call to launch. You work directly with the people who build your product, and the price we agree on is the price you pay.

  • Senior engineers only, assigned from day one
  • Fixed price, confirmed before any code is written
  • Weekly demos and full source-code ownership

Free scoping call. Fixed-price proposal within 24 hours.

Partners & Recognition

Certified Partner Status & Ratings

aws partner
network
Select Tech Partner
Rate on
Clutch 4.8
Microsoft
Silver Partner
Google Cloud
Partner
Teams we've built for
Pasqal
MAERSK
UnitedHealthcare
CNN
Mozilla Foundation
Huma
Alida
q
qPress
Emblazer
Go2ANDAMAN
homeloft
ACCESSTRUTH
Engagement Model

Four Phases. Four Weeks. Every Checkpoint is Working Software.

No status-report theatre. No slide decks. At every phase you receive something you can read, test, or deploy.

01

Data Audit and Assessment

We map your entire data flow: source systems, pipelines, warehouse setup, and analytics layer. You receive a written assessment: where data is breaking down, which platform (Snowflake or Databricks) fits your workload, and what the right architecture looks like.

02

Warehouse and Pipeline Build

We build or rebuild your data platform on Snowflake or Databricks according to the agreed architecture. Every pipeline is monitored, every transformation is documented, and every source system is connected with appropriate retry logic.

03

Validation and Analyst Handoff

We validate data accuracy end-to-end, reconcile numbers against source systems, and hand off to your analytics team with documented, trusted datasets. Analysts write SQL against clean tables instead of debugging raw exports.

04

Monitoring and Ongoing Support

We set up alerting and runbooks so your team can operate the platform independently. When you need to add new sources, fix a failing pipeline, or scale the warehouse, we are available on a retainer basis.

Testimonials

What Engineering & Product Leaders Say

Real feedback from our clients, from startups to large organisations.

4.8
Clutch · Verified Review
Fixed
Price guaranteed
10+
Industry verticals
NDA
Day one

“We had been trying to build a reliable analytics stack for 18 months. Enlight Lab came in, audited everything in a week, and had a working dbt layer in Snowflake within three weeks. For the first time, our analysts trust the data.”

Head of Data
Series B SaaS · Verified Client

“Enlight Lab delivered exactly what we needed, faster than we expected. Clear communication, strong technical judgment, and they understood our requirements without needing things repeated.”

Jay Joshi
Jay Joshi
CEO · Exar North

“Enlight Lab were excellent at execution, but what set them apart was their thinking on the product itself and the strategy around it. Real partners, not just developers.”

Sophia V. Prater
Sophia V. Prater
Founder, Rewired

“Enlight Lab took on a genuinely complex platform and delivered without the drama. They worked through every technical hurdle and suggested better ways to build along the way.”

Ben Christine
Ben Christine
Product Designer & Mentor

“Enlight Lab brings real breadth across product, engineering, and DevOps. They get everyone aligned and ship high quality work that holds up in production.”

Daniel Gallagher
Daniel Gallagher
Data Analytics & Engineering

From verified Clutch reviews and LinkedIn recommendations

Technology Stack

Enterprise-Grade Tools.
Battle-Tested in Production.

Data Platforms
SnowflakeDatabricksBigQueryRedshiftDelta Lake
Transformation & Orchestration
dbtAirflowDagsterFivetranAirbyte
Streaming & CDC
KafkaDebeziumAWS KinesisApache Flink
Analytics & Governance
MetabaseLookerModeAtlanOpenMetadata

Stack selection is driven by project requirements. We advise against over-engineering.

Free · No Obligation · NDA on Request

Tell Us About Your Project

30 minutes. We review your concept and send a fixed-price proposal within 24 hours of the call.

3 Weeks
To Trusted Analytics
<24hr
Proposal After Call
4.8★
Clutch Rating

What to expect on your scoping call:

  • Direct Engineering Scoping: Speak directly to a senior engineer. No salespeople, no scripted pitches.
  • Fixed-Price Quote: Receive a detailed written scope and a fixed-price quote within 24–48 hours.
  • Guaranteed Confidentiality: We sign a mutual NDA before we discuss any proprietary architecture or system logic.

Start With a Free Scoping Call

Tell us about your project and we’ll prepare a tailored scope and fixed-price proposal.

Your enquiry is confidential · NDA on Day 1 · We respond same business day

Or speak with a senior engineer directly:
Got Questions?

Frequently Asked Questions

Everything you need to know before booking a call.

Should we use Snowflake or Databricks?
It depends on your workload. Snowflake is the better choice for standard analytics, data warehousing, and BI workloads. Databricks is the better fit for data science, machine learning, and streaming analytics on Lakehouse architecture. We assess your specific workloads during the discovery call and recommend based on what you actually need, not a default preference.
What does a Snowflake or Databricks engagement cost?
Costs vary based on scope and complexity of your existing environment. Most engagements start with a fixed-scope audit and assessment, followed by a scoped build phase. We discuss budget and timeline during the discovery call and propose a structure that fits your situation.
How long does it take to get a data platform up and running?
A working warehouse with connected sources, basic dbt transformations, and validated reporting is typically achievable in three to six weeks, depending on the number of source systems and complexity of the transformations.
We already have a data team. Can you work with them?
Yes. Most engagements augment existing data teams rather than replace them. We help your engineers level up on Snowflake, Databricks, dbt, and pipeline architecture while delivering the core work.
Can you help us reduce our Snowflake or Databricks costs?
Yes. We have cut warehouse spend by 30–50% for several clients by optimising dbt models, eliminating redundant runs, right-sizing compute, and implementing clustering and partition strategies. The cost audit happens in the first week.
How do you handle data quality and testing?
Every dbt model we build includes schema tests, data tests, and column-level documentation. We set up dbt Cloud with CI/CD so that every pipeline change is tested before it runs in production. Your team knows when data breaks and why.
What about dbt? Do you use it?
Yes. Every transformation we build uses dbt with full documentation, testing, and version control. Your analysts inherit a clean, navigable data model. Without dbt, your transformations are undocumented SQL scripts with no lineage. With dbt, your team can actually trust the data.
Who owns the code and infrastructure at the end?
You do. All pipelines, dbt models, and infrastructure are transferred to your team at completion. We do not build proprietary platforms or create dependencies that require us to maintain.
How do I get started?
Book a free 30-minute discovery call. We will ask about your current data environment, your biggest pain points, and what Snowflake or Databricks implementation would actually unlock for your business. Within 24 hours of your call, we will outline a proposed engagement. No obligation.

Ready to Start Your Project?

30 minutes. No pitch deck. We review your concept, define the scope, and send a fixed-price proposal within 24 hours of the call.