Dedicated data engineers for your offshore team.
Offshore data engineers in Chiang Mai and Bangkok, working full time on your product and managed by us. A data engineer builds the pipelines that move data to where it can be used, and keeps them running when upstream systems change.
One agreement, one fixed monthly fee. We look after the people, and a service delivery manager keeps in touch with you about delivery.
This role is part of a dedicated data engineering team. It's staff augmentation, fully managed: take one role on its own, or the whole area as one delivery team.
One Data Engineer, assigned to your product and fully managed.
We assign a Data Engineer to your team full time and run everything around them: a service delivery manager who oversees delivery, training and coaching, the office and equipment, and HR and payroll. The price below is for a junior Data Engineer; other levels are priced in your proposal, and how the monthly fee is built explains the arithmetic.
From price
One junior Data Engineer, full time, everything below included. All 27 things included ››
- Data engineer From USD 2,500 per month
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Service
We manage and develop the team
- A service delivery manager who oversees operations and delivery
- A 1:1 with our Head of Delivery every two weeks
- Weekly delivery scoring and monthly capacity reports
- A Talent Success Manager for every team member
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HR
We are the employer
- Recruitment and technical assessment
- Employment contracts
- Salary and payroll
- Tax and social security
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Facilitation
We provide the workplace
- A desk in our office in Chiang Mai or Bangkok
- A Workplace Experience Manager on site
- Team events through the year
- IT support
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Equipment
We supply the tools
- Laptop and hardware
- Software licences
- LinkedIn Learning access
- Device security and management
What a Data Engineer does on a dedicated data engineering team.
They work in your cloud account and your warehouse and take requests from your analysts and product team. Once a load ships, they own it.
Data Engineer skills and technologies
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Building batch and streaming pipelines from source systems into your warehouse.
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Data quality testing and alerting, so a broken load surfaces before a report does.
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Pipeline maintenance as schemas change upstream, which is most of the ongoing work.
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Backfilling historical data when a pipeline changes shape, without double-counting.
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Managing schema evolution so a downstream model does not break silently on a new column.
Data Engineer seniority levels.
Junior to senior. Pipeline design choices show their effects months later, which is the case for an experienced engineer. The level you settle on is part of how the monthly fee is built.
When your team needs a Data Engineer.
The core data role, and usually the first one a team adds. Often joined by an analytics engineer or ETL developer as the work grows into a dedicated data engineering team. Companies that hire offshore developers for data work usually start here, because reliable pipelines come before analysis.
What we look for in a dedicated Data Engineer.
We look for data engineers who test data the way good developers test code. They should design pipelines that can be rerun safely, understand the warehouse cost of a careless query, and notice when a source quietly changes shape.
A remote Data Engineer's first three months on your team.
- Weeks 1 to 2Mapping your sources, pipelines and warehouse, and fixing the most fragile loads.
- Weeks 3 to 6Adding data quality tests and alerting, and building the next pipelines you have planned.
- Months 2 to 3Owning the pipeline estate, including schema changes and backfills.
Questions about adding a Data Engineer to your team.
Can you take over pipelines someone else built?
Yes, that's the usual starting point. The engineer we assign maps and documents what runs, where it breaks and who depends on it before improving anything. Fixes then come in priority order, starting with the pipelines whose failures hurt the business most, so trust in the data grows quickly.
Batch or streaming?
Batch, unless there is a real-time need. Nightly or hourly batch is simpler, cheaper and easier to debug for most reporting. Streaming makes sense for fraud detection, live inventory or user-facing features. The engineer designs it so the two approaches can share the same models.
Add remote data engineers to your team.
Tell us your sources, your warehouse and which loads break most often. We'll propose the data engineer profile we'd hire and the fixed monthly fee. Hired in four weeks from signing.
Tell us what your data engineer would work on.
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