Teams/Data
Data engineers
Pipelines, models, and warehouses your team can trust. Dedicated data engineers working from our Dhaka office, on your stack and your hours — on one US contract, at flat monthly rates.
prod · nightly-pipeline
01extract sources → synced
02transform models → built
03load warehouse → committed
04tests schema · freshness → passed
05dashboards → fresh
Ingest
streaming
Models
tested
Warehouse
loaded
Numbers nobody trusts are worse than no numbers.
When a pipeline breaks quietly, every dashboard downstream lies. Teams stop believing the data, then stop using it. That’s why we vet data engineers on modeling judgment and failure handling — not on how many tools they can name.
Pipeline reliability
Pipelines that run every night and tell you when they don't. Silent failures are the real enemy in data work.
Data modeling
Warehouse schemas that answer tomorrow's questions, not just today's. Clean models keep analytics fast and honest.
Quality tests
Schema, freshness, and volume checks on every model — so a bad load gets caught before it reaches a dashboard.
Orchestration
Dependencies, retries, and backfills handled properly. When one step fails, the rest waits instead of running on stale data.
Cost-aware processing
Warehouse bills grow quietly. We look for engineers who partition, prune, and schedule with the invoice in mind.
The stacks we staff.
Tell us what you run — we match from our pipeline. These are the data stacks we most commonly place.
| Stack | What we use it for | Where it shows up |
|---|---|---|
| Python | Ingestion, transformation, pipeline glue | Everywhere in the data stack |
| SQL | Modeling, analytics, warehouse work | Everywhere |
| Airflow / Dagster | Orchestration and scheduling | Pipelines with many moving parts |
| dbt | Tested, documented transformations | Warehouse-centric analytics teams |
| Spark | Large-scale batch processing | High-volume data, ML feature prep |
| BigQuery / Snowflake / Redshift | Cloud data warehouses | The analytics core of most stacks |
| Kafka | Streaming ingestion and events | Real-time products and event data |
What you'll see on Bangladeshi data CVs.
Certifications aren't how we vet — our pipeline is. But they show what the market here trains for. Behind them sits an engineering-school pipeline — BUET, University of Dhaka, NSU and others — and one of the world's most active competitive-programming communities.
| Certification | Issuer | What it signals |
|---|---|---|
| Professional Data Engineer | Google Cloud | Designing data systems on GCP |
| AWS Certified Data Engineer — Associate | Amazon | Pipelines and data stores on AWS |
| Databricks Certified Data Engineer Associate | Databricks | Spark and lakehouse fundamentals |
| dbt Analytics Engineering Certification | dbt Labs | Tested, version-controlled models |
| SnowPro Core | Snowflake | Snowflake platform fundamentals |
| CCDAK | Confluent | Building with Apache Kafka |
How we vet a data engineer.
Five stages before you meet anyone — and you still interview last and make the final call. Nobody joins your team without your sign-off.
- 1Pipeline design conversation
- 2Live SQL exercise
- 3Data-modeling depth
- 4Failure-handling walkthrough
- 5English & communication screen
Our office in Dhaka — where your team sits. Real photos, real people.
Frequently asked questions
With Girmairi, a dedicated mid-level data engineering seat starts at $3,000 per month, a senior seat is $4,200, and a lead seat is $5,000; junior seats are available on request. The flat rate includes office, equipment, HR, and management, and you're billed monthly in advance in USD. The full rate card is at /pricing#data-ai.
Yes. Girmairi places data engineers across the modern data stack — Python, SQL, Airflow and Dagster for orchestration, dbt for tested transformations, Spark for large-scale batch, and warehouses like BigQuery, Snowflake, and Redshift. Tell us what you run and we match from our pipeline.
A dedicated team means full-time engineers who work only for you, on your stack and your hours, rather than shared contractors juggling several clients. Girmairi's data engineers work from its managed office in Dhaka — company seats, equipment, and HR — while you direct the day-to-day work like any in-house team.
Every candidate goes through five stages: a pipeline design conversation, a live SQL exercise, a data-modeling deep dive, a failure-handling walkthrough, and an English and communication screen. You interview last and make the final call — nobody joins your team without your sign-off.
You contract with Girmairi LLC, a US company. Your NDA and IP assignment are signed with the US entity before any work begins, and you pay one monthly invoice in advance, in USD — the same as working with any US vendor.
Every seat comes with a replacement guarantee. If an engineer isn't the right fit, tell us and we replace them from our pipeline — a bad fit is our cost, not yours.
Yes. Teams that take 3 or more seats, or commit to 12 months, get 5–10% off the flat monthly rates. The same includes apply to every seat — office, equipment, HR, management, and the replacement guarantee.
Yes. Every client company gets one hour per month with Girmairi's founder — a working CTO — included at no extra cost. It's a standing channel for architecture questions, pipeline reviews, or planning how your data team should grow.
Data seats are on the standard rate card.
Same flat monthly rate, same includes — office, equipment, HR, management, replacement guarantee.