Moving data infrastructure to the cloud can change how an organisation stores, processes and uses its data. The technology matters, but the people delivering the migration can have just as much impact on its success.
Hiring the right Data Engineers therefore requires more than looking for experience with a particular cloud platform. Employers need to understand the migration itself, the existing data environment and the skills required to move between the two.
The right candidate should be able to work with the organisation’s current infrastructure while helping build a reliable and scalable future-state environment.
Understand What the Migration Actually Requires
Before recruiting, employers need a clear view of what the cloud migration involves.
A straightforward migration may require engineers to move existing pipelines and data workloads into a cloud environment. A larger transformation could involve redesigning data architecture, rebuilding pipelines, integrating new platforms and changing how teams access and use data.
Those differences have a direct impact on recruitment.
A Data Engineer who has experience maintaining cloud-based pipelines may be well suited to one project but may not have the architecture or migration experience required for another.
The hiring process should therefore start with the migration requirements rather than a generic Data Engineer job description.
Look for Relevant Cloud Experience
Cloud experience is likely to be important, but employers should be specific about what they actually need.
Experience with AWS, Microsoft Azure or Google Cloud can demonstrate familiarity with cloud environments, but the platform alone does not determine whether someone can successfully support a migration.
Candidates should be able to explain how they have used cloud technology in practice. This could include building data pipelines, managing storage, working with cloud databases, improving performance or supporting large-scale data processing.
The depth of experience matters more than simply having a cloud platform listed on a CV.
Assess Migration Experience
Cloud migration introduces challenges that do not necessarily appear in day-to-day data engineering.
Engineers may need to understand legacy systems, map existing data flows, identify dependencies and decide how workloads should move into the new environment. They may also need to manage migration risks while keeping existing services operational.
Candidates who have supported previous migrations can bring valuable experience because they understand that moving data is rarely just a matter of transferring files from one system to another.
During interviews, ask candidates to explain a migration they have worked on. What was the starting environment? What problems did they encounter? How did they approach dependencies, testing and data quality?
These questions can reveal far more than a list of migration technologies.
Assess Data Pipeline Skills
Data pipelines sit at the centre of many cloud migration projects.
Engineers may need to build new pipelines, adapt existing ones or move workloads between different platforms. They need to understand how data moves through the organisation and how changes to one part of the environment can affect another.
Look for candidates who can explain the design decisions behind their pipelines rather than simply naming the tools they have used.
Experience with technologies such as SQL, Python, ETL or ELT processes, orchestration and cloud data platforms may all be relevant, depending on the project.
The important question is whether the candidate can apply those skills to the organisation’s specific migration requirements.
Don’t Overlook Data Quality
A successful migration is not simply about moving data from one environment to another.
The organisation also needs confidence that the data remains accurate, complete and usable after the move.
Data Engineers may therefore need to identify inconsistencies, validate migrated data and build processes that detect problems before they affect users.
This makes data quality experience particularly valuable when assessing candidates.
Ask how candidates have previously identified or resolved data-quality problems. Their answers can help reveal whether they understand the wider impact of poor data rather than treating quality as a final testing exercise.
Consider Security and Governance
Moving data into the cloud can introduce new security and governance considerations.
The Data Engineer may work with sensitive customer, financial or operational information. Depending on the organisation and the project, they may need to understand access controls, encryption, data retention and regulatory requirements.
Employers should therefore consider these requirements when defining the role.
The UK’s 2026 Digital and Technologies Sector Skills Needs Assessment highlights the growing importance of data, cybersecurity and other digital capabilities as technology continues to change.
The level of security knowledge required will vary, but candidates should understand that data engineering decisions can have consequences beyond the technical environment.
Look for Problem-Solving Ability
Migration projects rarely follow the original plan perfectly.
Legacy systems may behave differently than expected. Data dependencies may be poorly documented. Performance can change after migration, while previously hidden quality problems can emerge during testing.
Strong Data Engineers need to investigate these problems and find practical solutions.
Interview questions should therefore explore how candidates have handled unexpected technical issues. Ask what happened, how they investigated the problem and why they chose their eventual solution.
This provides evidence of how they think rather than simply confirming that they have worked with a particular technology.
Seniority Matters
Not every cloud migration requires a senior Data Engineer, but larger or more complex projects may need people who can make decisions beyond individual pipelines.
Senior engineers may need to contribute to architecture decisions, establish engineering standards, review technical approaches and help less experienced team members.
They may also need to communicate with architects, project managers, security specialists and business stakeholders.
The more complex the migration, the more important it becomes to distinguish between someone who can execute defined tasks and someone who can help shape the technical approach.
Consider the Existing Technology Environment
The ideal candidate depends partly on what the organisation already has.
A business moving from on-premise SQL Server into Azure will have different requirements from an organisation migrating a large distributed data platform into AWS.
Existing technology, internal skills and the target architecture should therefore influence the recruitment profile.
This also prevents employers from creating unnecessarily broad specifications. Requiring experience across every major cloud platform, database technology and data tool may make the vacancy look comprehensive, but it can also exclude candidates who have the right transferable experience.
Decide What Can Be Learned
Cloud technology changes quickly, so employers should distinguish between skills that genuinely need to be present on day one and those that can be developed.
A candidate may have strong migration experience on Azure but little experience with AWS. Another may have extensive AWS experience but limited exposure to the organisation’s preferred data platform.
Neither should automatically be ruled out.
Strong data engineering fundamentals, problem-solving ability and experience working with complex data environments can transfer between technologies. The recruitment process should identify which gaps are manageable and which would create a genuine delivery risk.
Use Practical Technical Assessments
Technical assessments can help employers test whether candidates can apply their experience to a realistic migration problem.
Rather than asking candidates to recall definitions, give them a scenario. They might need to explain how they would approach moving a legacy data pipeline into the cloud, identify potential risks or suggest how they would validate the migrated data.
The aim is not necessarily to find one perfect answer.
A strong assessment should reveal how the candidate thinks, what questions they ask and whether they recognise the technical and business consequences of their decisions.
Hire for the Migration You Actually Have
There is no single Data Engineer profile that fits every cloud migration.
A small migration may need an experienced engineer who can execute a well-defined technical plan. A complex transformation may require senior engineers who can work across architecture, data, security and delivery.
The recruitment process should reflect that difference.
Employers that define the migration first can build a much more accurate candidate profile. They can then assess candidates against the skills that genuinely matter rather than relying on long technology lists or generic cloud experience.
What Should Employers Look for in a Data Engineer for Cloud Migration?
The strongest candidates combine solid data engineering fundamentals with relevant cloud experience, problem-solving ability and an understanding of migration challenges.
They should be able to explain their previous work, understand the impact of their technical decisions and adapt their approach when the environment changes.
For employers, successful hiring starts before the vacancy is advertised. Understanding the migration, identifying the capabilities required and separating essential skills from those that can be learned will create a stronger basis for finding the right Data Engineer.
A good cloud migration depends on good technology, but it also depends on having the right people to move it forward.
