Dedicated data engineering team.
Offshore data engineers, analytics engineers and database administrators work only on your data platform, as a dedicated data engineering team. They are on our payroll, picked for the warehouse and tools you already have, and work from our offices in Chiang Mai and Bangkok, Thailand. They build in your warehouse and your cloud account. You decide which numbers matter first.
What you get and what you pay.
Azendo employs the data engineers we assign and gives them an office, hardware and regular coaching. Through staff augmentation or offshore staffing you would arrange the onboarding, reviews and growth yourself. Here a service delivery manager tracks what the team delivers, with a delivery report every month.
Price examples
Junior level, full time, everything below included. Mid-level and senior levels are priced in your proposal. All 27 things included ››
- Data engineer From USD 2,500 per month
- Analytics engineer From USD 2,500 per month
- ETL developer 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 the monthly fee for data engineers includes.
You agree a monthly capacity in hours with us. The fee covers the data engineer's salary and every layer around it: the service delivery manager who oversees delivery, training and development, the workplace, the equipment and the HR behind the employment. It is the same amount every month.
- One agreement and one invoice, with no upfront fee or management surcharge
- Holidays are already priced in, so April and May cost the same
- A capacity report every month, so you see the hours delivered
Data engineers matched to your warehouse.
We search for the warehouse, orchestration and modelling tools you already use, and we test each candidate before you meet them.
- Roles and seniority
- Stack and domain
- Way of working
- Capacity and time to hire
- 25 Week 1 Sourcing Headhunted for your brief
- 12 Week 2 AI processing and screening Matched to your stack
- 5 Week 3 Technical testing Pass technical testing
- 1 Week 4 Mindset, culture and logic Proposed to you
Data engineers and the roles beside them.
Pipeline, analytics, ETL and database work each have a page below. Data scientists, MLOps and AI engineers can join as the data team grows into models and AI.
What a dedicated data engineering team builds and maintains.
Companies hire offshore data engineers when reports disagree, pipelines fail quietly and every new data source takes months to connect. Data engineering outsourcing often means a one-off build that someone else has to run afterwards. A dedicated data engineering team builds the pipelines and then keeps running them. The offshore data engineers we assign stay on your platform, own its monitoring and learn which numbers your business relies on.
- Pipeline developmentIngestion and transformation in Airflow, dbt or Prefect, from every source your business uses.
- Warehouse modellingModels in Snowflake, BigQuery or Databricks that analysts and dashboards can trust.
- Data quality and testingTests on every model, so a broken source shows up before a wrong number does.
- Monitoring and alertingFreshness and volume checks with alerts that reach the right person.
- StreamingKafka, Spark or Flink where the business needs data in minutes, not overnight.
- Documentation and lineageWhere each number comes from, written down and kept current.
Stacks we work in
We hire for your data stack. These are frequent requests, and a tool that is not listed simply goes into the brief.
- Airflow
- dbt
- Python
- Fivetran
- Prefect
- Snowflake
- BigQuery
- Redshift
- Databricks
- ClickHouse
- Kafka
- Spark
- Docker
- Flink
- RabbitMQ
What a dedicated data engineering team is.
A dedicated data engineering team is a group of engineers who build and maintain one company's pipelines, warehouse and data models, full time. They work in your cloud account and your tools. You decide which data matters first, and Azendo manages the engineers and answers for delivery.
Where it pays off most
It pays off when reports disagree, pipelines break without anyone noticing, or analysts spend their days preparing data. The same engineers stay with your warehouse and your models, so fixes hold and each new source builds on the last one.
Who is on the team
- Data engineerPipelines, models and data tests
- Analytics engineerThe modelling layer your analysts use
- ETL developerMovement of data between systems
- Database administratorPerformance, backups and access
- Service delivery managerOversees delivery on our side and reviews it with you every two weeks
- Talent Success managerFor every specialist: a quarterly development plan and coaching tailored to it
- Your product ownerSets the priorities and accepts the work
Other ways to build a data engineering team, compared.
| Dedicated team, Azendo | Staff augmentation | Project outsourcing | |
|---|---|---|---|
| What you buy | Agreed monthly capacity from people who work only on your product | A person's hours, billed by the hour or the month | A defined scope, at a fixed price or on time and materials |
| Who manages the team | Azendo, day to day, with you setting the priorities | You do, day to day: Azendo's estimate is four to eight hours a week per specialist | The vendor's project manager |
| Who answers for delivery | Azendo, scored by you every Friday | You do | The vendor, against the agreed scope |
| How long people stay | On your product, and with Azendo for 3.3 years on average | Until the contract ends | Until the project is handed over |
| Best fit | A data platform that keeps gaining sources, users and questions | A short gap in a team you already run | One project with a clear end |
"We are 100% committed in a partnership. We go above and beyond, which is why we can say that it is truly a managed service we offer."
Mikkel Schmidt, CEO and founder
Questions about a dedicated data engineering team.
What does a dedicated data engineering team do?
A dedicated data engineering team builds and runs the data platform behind your reports and models full time: pipelines, warehouse models, data quality tests and monitoring. With Azendo the engineers are ours, managed from Chiang Mai and Bangkok, and they work in your warehouse and your cloud account.
How much does it cost to hire offshore data engineers this way?
Data engineers, analytics engineers, ETL developers and database administrators start from USD 2,500 per month at junior level, full time. Each data engineer's fee also covers delivery management, a Talent Success Manager and training, the office and equipment, and HR and payroll. See how the monthly fee is built.
Does our data stay in our own systems?
Yes. The engineers work in your warehouse, your cloud account and your repositories, under your access rules, and nothing is copied to systems of ours. The data, the models and the pipeline code stay yours, and you can change or revoke access at any time.
Can the team work with the stack we already have?
Yes. Snowflake, BigQuery, Redshift and Databricks are the warehouses we see most, with dbt, Airflow and Fivetran around them and Kafka or Spark where data has to move fast. The engineers start from what you run and improve it before suggesting anything new.
Where does a data engineering team usually start?
With the pipelines behind the numbers your business watches most, such as revenue, churn or stock levels. The engineers map what feeds those reports, add tests and monitoring, and fix what breaks before they build anything new. New sources follow once the foundations hold.
How does data engineering work with data science and AI?
Data scientists and AI engineers depend on clean, current data, so data engineering usually comes first. A dedicated data science team or AI engineers can join under the same agreement once the foundations are in place.
How quickly can you hire the engineers?
Our time to hire is four weeks from signing. We agree it with you first, look for engineers who know your warehouse and orchestration tools, and introduce them before anything is committed. You pay nothing until an engineer has had their first day on your platform.
Do the data engineers work remotely?
Yes. Azendo employs them offshore and assigns each one to you full time, to work in your warehouse, your cloud account and your orchestration tools. They are in our offices most days, and at home on up to two, through a secure VPN.
Service areas that often join a data engineering team.
Each role joins under the same agreement, works in the same sprints and reports to the same service delivery manager. You add one when your product calls for it.