Data Mesh Without Organizational Chaos
Shift data ownership to domain teams without creating silos, duplicate datasets, or definitions that don't match across the org.
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Trusted and top rated tech team
Decentralize data without losing control
Central data teams become bottlenecks. Every request is a ticket, every report takes months, and business units build shadow systems just to get work done. Data mesh fixes this by shifting ownership to domains, but only if you have the governance, platform, and standards to prevent fragmentation. We help you get decentralization right.
Our capabilities include:
- Data mesh architecture design and implementation
- Domain data product definition and ownership models
- Federated governance framework development
- Self-serve data platform setup
- Data discoverability and catalog integration
- Organizational change and adoption planning
Who we support
Central data teams can’t scale forever. We help organizations shift to domain ownership with governance that keeps data consistent and searchable.
Organizations With Data Bottlenecks
Every analytics request goes through the same overwhelmed data team. Business units wait weeks for reports and build workarounds to get anything done. Putting domains in charge distributes the load so your central team stops being the blocker.
Companies With Inconsistent Data
Different teams define metrics differently. Sales says revenue is one number, finance says another. Federated governance establishes shared definitions while letting domains own their data products.
Enterprises Scaling Data Operations
You're adding domains, acquiring companies, and your centralized architecture can't keep up. A mesh approach scales by distributing responsibility while maintaining discoverability and standards across the organization.
Ways to engage
We offer a wide range of engagement models to meet our clients’ needs. From hourly consultation to fully managed solutions, our engagement models are designed to be flexible and customizable.
Staff Augmentation
Get access to on-demand product and engineering team talent that gives your company the flexibility to scale up and down as business needs ebb and flow.
Retainer Services
Retainers are perfect for companies that have a fully built product in maintenance mode. We'll give you peace of mind by keeping your software running, secure, and up to date.
Project Engagement
Project-based contracts that can range from small-scale audit and strategy sessions to more intricate replatforming or build from scratch initiatives.
We'll spec out a custom engagement model for you
Invested in creating success and defining new standards
Why choose Curotec for data mesh architecture?
Our engineers understand that data mesh is mostly organizational change, not just technology. We design domain ownership models, federated governance, and self-serve platforms that actually get adopted instead of creating a different kind of mess than the one you’re escaping.
1
Extraordinary people, exceptional outcomes
Our outstanding team represents our greatest asset. With business acumen, we translate objectives into solutions. Intellectual agility drives efficient software development problem-solving. Superior communication ensures seamless teamwork integration.
2
Deep technical expertise
We don’t claim to be experts in every framework and language. Instead, we focus on the tech ecosystems in which we excel, selecting engagements that align with our competencies for optimal results. Moreover, we offer pre-developed components and scaffolding to save you time and money.
3
Balancing innovation with practicality
We stay ahead of industry trends and innovations, avoiding the hype of every new technology fad. Focusing on innovations with real commercial potential, we guide you through the ever-changing tech landscape, helping you embrace proven technologies and cutting-edge advancements.
4
Flexibility in our approach
We offer a range of flexible working arrangements to meet your specific needs. Whether you prefer our end-to-end project delivery, embedding our experts within your teams, or consulting and retainer options, we have a solution designed to suit you.
Data mesh capabilities for domain-driven data
Domain Ownership Design
Data Product Development
Federated Governance
Self-Serve Platform
Data Discoverability
Adoption & Change Management
Tools and technologies for data mesh architecture
Data Catalogs & Discovery
Our engineers implement catalogs that make data products discoverable so teams find what exists before building duplicates.
- DataHub — Open-source metadata platform with search, lineage, and governance features for discovering data products across domains
- Atlan — Modern data catalog with collaboration features, automated lineage, and integrations across the data stack
- Collibra — Enterprise data intelligence platform with catalog, governance workflows, and business glossary management
- Alation — Data catalog with behavioral analytics that surfaces popular datasets and tribal knowledge from query patterns
- AWS Glue Data Catalog — Managed metadata repository for AWS with schema discovery and integration across analytics services
- Google Data Catalog — Fully managed service for metadata management with search, tagging, and policy enforcement in GCP
Data Product Platforms
Curotec builds platforms that let domain teams create, document, and serve data products with consistent interfaces.
- Databricks Unity Catalog — Unified governance layer for data and AI assets with fine-grained access control and cross-workspace discovery
- Snowflake Data Marketplace — Platform for sharing and monetizing data products with built-in governance and secure data exchange
- dbt — Transformation framework that treats data models as code with documentation, testing, and lineage built in
- Starburst — Query engine for distributed data with data product creation features and access control across sources
- Nexla — Data product platform for creating, monitoring, and sharing data flows with self-service interfaces for domain teams
- Informatica — Enterprise data management platform with data product capabilities, quality monitoring, and catalog integration
Governance & Policy Automation
We implement governance tools that enforce standards automatically without requiring central team approval for every action.
- Immuta — Data access control platform with policy automation, dynamic masking, and audit logging across platforms
- Privacera — Unified governance with automated policy enforcement, access control, and compliance reporting across data sources
- Apache Ranger — Centralized security framework for Hadoop ecosystem with fine-grained authorization and audit capabilities
- Satori — Data security platform with just-in-time access, dynamic masking, and continuous compliance monitoring
- Open Policy Agent — Policy engine for enforcing authorization rules across services, APIs, and infrastructure as code
- Purview — Microsoft governance solution with automated classification, lineage tracking, and policy management across Azure
Self-Serve Infrastructure
Our teams configure infrastructure that lets domains provision storage, compute, and pipelines without filing tickets.
- Terraform — Infrastructure as code for provisioning cloud resources with modules that domain teams can reuse without deep expertise
- Backstage — Developer portal with software templates that let teams spin up data infrastructure through self-service workflows
- AWS Service Catalog — Managed portfolios of approved infrastructure that domain teams provision without direct console access
- Crossplane — Kubernetes-native infrastructure provisioning that lets teams request resources through familiar YAML definitions
- Azure Purview Data Map — Self-service data estate management with automated scanning and classification across Azure resources
- Pulumi — Infrastructure as code using general-purpose languages so teams build reusable components for data platform provisioning
Data Quality & Observability
Curotec integrates quality checks and monitoring so domain teams know when their data products break or drift from standards.
- Great Expectations — Data validation framework with automated testing, documentation, and profiling for data product quality checks
- Monte Carlo — Data observability platform with anomaly detection, lineage-based impact analysis, and automated incident alerts
- Soda — Data quality testing with SQL-based checks, monitoring dashboards, and integration into CI/CD pipelines
- Bigeye — Automated data quality monitoring with anomaly detection, root cause analysis, and SLA tracking for data products
- Datafold — Data diff and regression testing that catches quality issues before they reach production data products
- Ataccama — Data quality platform with profiling, cleansing, and monitoring capabilities for enterprise data governance
Metadata & Lineage Management
We set up lineage tracking so teams understand where data comes from and what downstream products depend on it.
- OpenLineage — Open standard for lineage metadata collection with integrations across Airflow, Spark, and dbt pipelines
- Marquez — Open-source lineage server built on OpenLineage for tracking data flows and dependencies across jobs
- Apache Atlas — Metadata management and governance with lineage visualization, classification, and glossary features for Hadoop
- Egeria — Open metadata framework for exchanging metadata across tools and platforms with federated governance support
- Amundsen — Open-source data discovery platform with lineage integration, usage statistics, and owner information
- Stemma — Managed data catalog built on Amundsen with lineage tracking, quality scores, and collaboration features
FAQs about our data mesh services
Is data mesh right for our organization?
Data mesh fits large organizations with multiple domains generating analytical data and bottlenecked central teams. Smaller companies with simple data needs often do better with centralized approaches. We assess fit before recommending mesh.
How long does data mesh implementation take?
Initial pilots with one or two domains take a few months. Full organizational rollout takes a year or more because the cultural and process changes take longer than the technology. We phase implementation to show value early.
What happens to our central data team?
They shift from building everything to enabling domains. They own the self-serve platform, set governance standards, and help domain teams succeed. It’s a different role, not elimination.
How do you prevent domains from creating silos?
Federated governance with shared standards, a common catalog for discoverability, and data contracts that enforce interoperability. Domains own their data but follow rules that keep everything connected.
Do domain teams need to become data engineers?
Not fully. Self-serve platforms reduce the technical burden, and data product templates standardize common patterns. But domains do need people who understand their data well enough to own its quality and documentation.
How is data mesh different from a data lakehouse?
Lakehouse is a technology architecture for storage and compute. Data mesh is an organizational model for ownership and governance. You can implement mesh on top of lakehouse infrastructure.
Ready to have a conversation?
We’re here to discuss how we can partner, sharing our knowledge and experience for your product development needs. Get started driving your business forward.