Sebastian Group / Case Studies

Case Studies

Building the team behind the transformation.

Manufacturing / Cloud / Data / AI

Representative searches, drawn from real engagements. Client names withheld for confidentiality.

Azure cloud foundation

Building the leadership and engineering team behind a manufacturer's move to Azure

This manufacturer needed more than Azure engineers. It needed someone to own the cloud strategy and a group of builders who could stand up a secure platform for data, ERP and AI.

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Databricks lakehouse

Hiring the leaders and builders who turn Databricks into a real enterprise data platform

This manufacturer had already picked Azure Databricks. What it still needed was the leadership, architecture and engineering talent to connect ERP and plant data and ship data products people actually use.

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Snowflake data cloud

Building the team to grow Snowflake across functions and business units

This manufacturer wanted Snowflake to do more than reporting. We helped define and hire the leadership, architecture and engineering talent to run it as an enterprise data cloud.

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ERP data consolidation

Hiring the cross functional team that turns scattered ERP data into one trusted source

Several ERP systems were blocking a clear view across finance, supply chain and manufacturing. We helped the client define and hire the leaders, architects and builders to bring that data together without losing its business meaning.

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Manufacturing AI

Helping a manufacturer move AI out of pilots and into the plant

This manufacturer had good AI ideas but not the mix of data science, engineering and plant know how to deploy them and make them stick.

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Smart factory

Hiring the IT, OT and engineering talent to scale smart factory programs

This manufacturer had automation experts inside its plants and cloud experts in corporate IT. What it did not have was a team connecting the machines, the plant systems, the data platforms and the business.

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Enterprise governance

Helping a manufacturer turn data governance from policy into something that actually works

This manufacturer had governance policies on paper. What it lacked were the leaders, architects, engineers and owners to make trusted data available across the business.

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How the cases fit together

The seven case studies tell one story about building manufacturing teams.

Leadership, builders and business outcomes across the seven case studies
Program	Leadership	Core builders	Business outcome
Azure cloud foundation	VP Infrastructure, Cloud Director	Platform, network, DevOps, SRE and security engineers	Secure, scalable base for ERP, data and AI
Databricks lakehouse	Head of Data Platform	Data, Spark, streaming and platform engineers	Trusted data products, ready for AI
Snowflake data cloud	VP Data, Platform Director	Snowflake, dbt, ELT and DataOps engineers	Cross functional analytics, sharing and scale
ERP data consolidation	ERP/Data Transformation Director	SAP, CDC, MDM, modeling and reconciliation engineers	One trusted view across finance, supply chain and plants
Manufacturing AI	Director of Manufacturing AI	Data scientists, ML and AI application engineers	Production AI for maintenance, quality and operations
Smart factory	VP Digital Manufacturing	MES, IoT, streaming, controls and OT security engineers	Connected plants and scalable Industry 4.0
Enterprise governance	CDO, Governance Director	Metadata, quality, MDM and access control engineers	Trusted, reusable, governed data

The Sebastian Group difference

The thread through every case is the same. We connect four things:

The outcome the manufacturer needs to improve
The environment it runs in: cloud, data platform, ERP, plant systems and security
The team it takes: leaders, architects, builders and domain owners
The proof: what each candidate has personally built, led, deployed and improved

How we build the team

We define the shape of the team the initiative actually needs, not just the open role.
We validate the real resource requirement with the client.
In most searches we identify roles the client had not considered.
We right-size the team, and where AI can now handle about 30 percent of the work we reduce the headcount accordingly.

Positioning statement

Sebastian Group helps manufacturers and retailers build the leadership and technical teams behind cloud, data and AI work. We do not start with a list of job titles. We start with the business outcome, the systems involved and the work that has to get done. From there we define and hire the right mix of leaders, architects, engineers, data scientists and domain talent, people who can work across cloud, ERP, plant systems and the business to get the initiative into production.

Why clients work with us

Better role design before a single search begins
A clear line between must have skills and skills that can transfer
No unrealistic "unicorn" job descriptions
The right balance of leaders and builders
Candidates judged on what they shipped and the results, not keywords
Internal teams and consulting partners pulling in the same direction
Skills that stay in house after the first project is done
A hiring model you can reuse for the next platform, plant or use case