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Cluj-Napoca · Romania · Est. 2019

Engineers who think
like your team.

Dapter is a specialist data engineering practice. We don't sell tool licences or run workshops — we send senior engineers to work inside your organisation and build the infrastructure your data strategy depends on.

10PB
Data processed monthly
<40ms
Median stream latency
3
Major cloud platforms
100%
Project delivery rate
Who we are

More than
an agency.
A practice.

Dapter was founded on a simple conviction: data engineering done well requires deep involvement, not just deliverables. From day one, our engineers embed directly inside client teams — joining standups, contributing to architecture decisions, and taking ownership of outcomes rather than scoping against them.

We are not a generalist technology firm. Every engineer at Dapter specialises in the modern data stack: ingestion frameworks, distributed compute, storage layer design, orchestration, and the APIs that serve data to the people and systems that need it. When you engage Dapter, you are hiring engineers with years of hands-on production experience — not a project manager who coordinates juniors.

"A successful data implementation is built on the foundation of a solid, honest, and transparent relationship — not just good code."

Our base in Cluj-Napoca, Romania gives us access to some of Eastern Europe's strongest engineering talent. Our engineers hold recognised certifications across AWS, GCP, Azure, Snowflake, and Databricks, and every hire passes a rigorous multi-stage technical process before joining a client team.

Why Dapter

The standards
we hold
ourselves to.

These are not aspirational values on a slide — they are the operational principles that govern every engagement, every code review, and every production deployment we are responsible for.

01

Code quality as a discipline

Regular code reviews, cross-reviews, SonarQube static analysis, and traceability matrices are not optional at Dapter — they are the baseline. Every pipeline we ship is designed to be maintained, extended, and understood by your team long after we have handed it over.

02

Engineers with genuine depth

We hire only senior engineers who demonstrate rigorous platform knowledge through a multi-stage technical process. Every Dapter engineer arrives with a clear professional development roadmap, holds recognised certifications, and is fluent in English across technical and business contexts.

03

Embedded by design

Our engineers don't work in isolation behind a ticket queue. They join your standups, own OKRs, participate in architecture reviews, and function as indistinguishable members of your data platform team — until the work is production-ready and the knowledge transfer is complete.

04

Investment in R&D

We allocate a meaningful share of our revenue to internal research and experimentation. Before we recommend any tool or architectural pattern to a client, we have already pressure-tested it in our own environment. Our advice is earned, not forwarded from a vendor whitepaper.

05

Outcomes over outputs

We don't measure success by lines of code or tickets closed. We measure it by pipeline reliability, data freshness SLAs, query latency, and the quality of business decisions your team can make because of the infrastructure we built together. Technology is the means, not the goal.

06

Delivery you can rely on

On-time, on-scope delivery is a professional obligation at Dapter, not a marketing claim. We maintain clear communication throughout every engagement, surface risks before they become blockers, and do not ship work we would not put our name on. Every project we have undertaken has been delivered.

How we engage

From first call
to production.

01
Discovery & architecture review
We begin with a structured review of your current data landscape — ingestion points, storage layers, compute patterns, and the business questions your data needs to answer. We identify gaps, risks, and quick wins before writing a line of code.
02
Embedded team placement
The right engineers are assigned based on your stack and objectives. They integrate with your team's workflows, tools, and communication channels — not a separate workstream that presents updates at fortnightly check-ins.
03
Iterative build & delivery
Work is delivered incrementally with production deployments at every milestone. Every component is peer-reviewed, instrumented for observability, and documented before it is handed over. We don't accumulate debt to hit deadlines.
04
Knowledge transfer & handoff
Engagements end with your team fully in control. That means runbooks, architecture documentation, operational playbooks, and live walkthrough sessions — so the infrastructure we built continues to perform without a dependency on Dapter.
Core stack
Apache Spark Apache Kafka Apache Flink Apache Airflow Delta Lake Apache Iceberg dbt Snowflake Databricks AWS EMR Google BigQuery Azure Synapse MLflow GraphQL REST APIs Unity Catalog Delta Live Tables Snowpark
We don't arrive with a pre-packaged solution. We arrive with engineers who learn your problem before they propose the architecture.
— Dapter Engineering Practice
Start the conversation

Ready to build
something serious?

Whether you're scaling an existing pipeline or building your data platform from scratch, we'll meet you where you are and engineer the architecture you need.