See where data migration, modernisation and managed services are heading

For data leaders and service-line heads planning platform moves, operating models and talent for the next two to three years.

Engagement type: Solo Pod
Experts: 1 lead · 2 consulted
Hours: ~35
Duration: 3 weeks

What the client needed

A firm needed a current view of data migration, modernisation and data managed services: how demand and delivery are shifting, which source-to-target patterns dominate, how operating models are changing, what agentic AI and Gen AI are doing to the work, and how platforms and talent models are likely to evolve.

The experts engaged

Previously at Tech Mahindra, LTIMindtree, TCS, Cognizant · 18 years

Roles helddelivery head and principal data architect · advisory data consultant · senior cloud data architect

Data-migration and modernisation programmes for global clients, including a UK investment bank
Ran a 120-member data-engineering team

Atlas Verified · Tier B

Previously at Persistent, TCS, Accenture · 14 years

Roles heldsenior data architect · data architect, Gen AI, Snowflake and database transformation

Snowflake-certified; lakehouse and data-mesh builds on cloud
Three years applying Gen AI to data-engineering productivity

Atlas Verified · Tier C

Previously at EY, Cognizant, HCL Technologies · 17 years

Roles heldassociate director, technology strategy · practice lead, cloud and IoT

Cloud and data platform strategy for enterprise clients
Operating-model design for data managed services

Atlas Verified · Tier B

A exceptional · B strong · C competent — the tier is derived from the whole assessment, not a single score. The transcript and report are open to you before you engage. How verification works →

The brief

The questions on the table

As the client wrote them, lightly shortened. Client and respondents are not named.

Q1
How are demand, delivery and the main challenges shifting in data migration, modernisation and managed services?
Q2
Which source-to-target migration patterns dominate now, and what operating models go with them?
Q3
What are agentic AI and Gen AI changing in data-platform work, and what is still hype?
Q4
How will platforms and talent models look in two to three years?

The hours

What the work involved

01
Demand and delivery
Where the work is coming from, what clients ask for now versus two years ago, and where delivery struggles, from the lead’s recent programmes.
02
Migration patterns
The source-to-target patterns actually being run — legacy warehouse to cloud, Hadoop to lakehouse, platform consolidation — with the operating model each tends to need.
03
AI in the work
What Gen AI and agentic tooling are doing in migration, pipeline build and run support, with measured effects where the experts had them.
04
Cross-check
Two further architects — Snowflake-certified and enterprise-data — reviewed the pattern and AI findings.
05
Working session
With the client’s data practice leadership.

Deliverables

What the client received

Trend noteDemand, delivery, challenges.
Pattern catalogueSource-to-target, with operating models.
AI impact noteMeasured where possible.
OutlookPlatforms and talent, two to three years.
One working sessionWith notes.

The terms

What an engagement like this costs

You buy hours in blocks and can change the expert at the end of any block, at no extra cost. Longer projects run in stages: pause after a block, pick up the next stage when you are ready.

Pricing in full →

Rate band: $65–$250 /hr; Senior specialists can be up to $500
Hour blocks: 1 · 2 · 5 · 10 · 20 · 50 · custom
This engagement: Solo Pod · ~35 hours · 3 weeks

Planning a data platform move?

Describe what you need

For example: “We run a data managed-services practice and need to see how AI and new platforms will change our offer by 2028.”

We aim to come back with matched experts within 24 to 72 hours.