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Request Multiple Quotes from Data Engineering Companies | RFQmatch.com

Found 12 suppliers in this category

Request multiple quotes from top Data Engineering companies on RFQmatch.com. Compare experts, save time, and find the right data engineering partner fast.
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Altius Vendor Assessment Ltd

Derby, United Kingdom

Altius Vendor Assessment offers Database Services and Database activities with a focus on database management, database administration, data integration, data governance, cloud databases, relational databases, SQL optimization, performance tuning, database security, backup and disaster recovery, data migration, and enterprise-grade data solutions. It is easy to get in touch or request a quote through RFQmatch.com.

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Arrola

Netherlands

Arrola�s current products/services. Please provide key details, or I can give a generic, non-specific description that may not be accurate.

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De Ulebelt

7425 NC DEVENTER, Netherlands

current products/services. If you paste key offerings, I�ll craft a concise, staccato description in English.

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Diagnostic Alliance

08013, Spain

Diagnostic Alliance leverages an international network of senior healthcare IT consultants to deliver vendor-neutral image management solutions anchored in robust, industry-standard open source technology deployed across hundreds of production sites worldwide. Through a vendor-neutral VNA and OSS approach, Diagnostic Alliance enables: - substantial reduction of archiving costs, whether on-site or cloud-based - access to advanced imaging applications beyond those offered by conventional PACS vendors - optimized clinical workflow and operational efficiency - standards-based interfacing and interoperable data communication - enhanced control over image data and lifecycle management Easy to get in touch or request a quote through RFQmatch.com.

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Elmicron Dr. Harald Oehlmann GmbH

Naumburg, Germany

Elmicron Dr. Harald Oehlmann is a leading provider of labeling and data capture solutions leveraging barcode, Datamatrix, and RFID technologies across healthcare, automotive, industry, and logistics sectors. Our Auto-ID expertise contributes at the European level through participation in standardization groups for Automatic Data Capture. With over 20 years of experience, we serve as a premier partner for customers implementing identification system projects, delivering system solutions tailored to individual requirements and a comprehensive service portfolio—from labels and printing technology to reading technology and complete custom system solutions. Our specialists ensure the seamless integration of Elmicron modules for clear product identification and traceability, enabling efficient identification and traceability across supply chains. We are specialists in UDI labeling for medical devices and offer expert presentations and workshops at an international level. Easy to get in touch or request a quote through RFQmatch.com.

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Enterium Sp. Z O.O.

Chorzow, Poland

Enterium is an experienced team of experts in finance, controlling, data flow automation, and cloud-based reporting and visualization, delivering centralized, reliable, interactive BI-class dashboards that form a solid foundation for data-driven decision making. With over 20 years of market presence across diverse industries and business models, Enterium combines deep knowledge of financial and business processes with extensive technology and database expertise. Satisfied clients maintain long-term collaborations, recognizing the added value and quality of Enterium. Our comprehensive end-to-end approach covers data generation in accounting and operations, data flow and preparation, automation, and ongoing maintenance of high-quality current reports adapted to evolving needs. Enterium partners with Microsoft to support data flow, collection, transformation, and analysis processes, ensuring visibility and control over organizational efficiency and achievement of operational and strategic goals. Easy to get in touch or request a quote through RFQmatch.com. Keywords: Power BI, DataDriven, Controlling, CFO, Dashboards, cloud reporting, BI, analytics, finance, data automation, data governance.

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FAME B.V.

Zwolle, Netherlands

current offerings. Do you want me to fetch it, or can you paste the key products/services? I�ll then provide a short, staccato, concise description in English.

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Financial Data Management Plc

E16 4ES, United Kingdom

Financial Data Management delivers leading print and mail solutions and comprehensive document services for public and private sector organisations. Our core offerings include transactional, operational, and marketing document solutions featuring bulk variable data printing and mailing, ad hoc and specialist printing, and hybrid mail. In-house designers and typesetters optimize artwork to meet diverse client requirements, from personalised correspondence to forms and brochures across printed and electronic mediums. We specialise in mailing customer-critical communications such as bills, statements, and voting documentation with 100% reconciliation and a guaranteed no-fail postage date. Data Services: our specialist programmers and processors manipulate data in any format and develop bespoke routines to fully automate data processing. Easy to get in touch or request a quote through RFQmatch.com.

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Oscivers B.V.

8017 BW ZWOLLE, Netherlands

I don�t have reliable data about Oscivers B.V.�s products or services. If you provide the text or key details from their site, I�ll deliver a concise English description.

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RAETH

Zwolle, Netherlands

I can�t access raeth.nl right now to verify their products/services. I don�t have reliable, up-to-date data on RAETH. If you paste key points or a page snippet, I�ll produce a concise, staccato-style description in English.

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Tegmento BV

Raalte, Netherlands

right now and don�t have verified details on Tegmento BV�s products or services. If you provide the information or allow me to summarize from another source, I�ll craft a concise English description.

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WeKaDATA BV

RAALTE, Netherlands

WeKaDATA BV � Dutch data services and solutions. Core offerings: - Data strategy and governance; data architecture and modeling - Data integration; ETL/ELT; data migration; data pipelines - Data warehousing and data lakes; cloud platforms (e.g., public/private clouds) - Data quality, profiling, cleansing, enrichment; metadata management - Real-time/streaming data processing; event-driven architectures - Analytics and business intelligence; dashboards; reporting - Data science and AI/ML; models, analytics-ready data - Data engineering and cloud modernization; migration to modern platforms - Managed data services; monitoring, maintenance, support - Training and advisory services; workshops, capability building Note: this reflects typical offerings for a Dutch data services firm; for exact, up-to-date details, consult their site or contact them.

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Data-ServicesBusiness Intelligence & DashboardsData GovernanceData Science & ModelingData Warehousing

About Request Multiple Quotes from Data Engineering Companies | RFQmatch.com

In today’s competitive business landscape, organizations across every sector are under constant pressure to improve performance, visibility, efficiency, and growth. Effective Data Engineering helps turn fragmented information into trusted, actionable data that supports smarter decisions and stronger execution. This matters for Owners, CEOs, COOs, C-level executives, procurement leaders, vendor managers, and operational managers who need dependable data foundations to drive business outcomes with confidence.

Our offering is designed to streamline sourcing and onboarding, simplify workflows, reduce risk, and support scalable operations as data demands grow. By improving responsiveness, data integrity, compliance defensibility, and reliability, it helps businesses reduce internal effort while strengthening confidence in reporting, analytics, and day-to-day operations. The result is a more efficient and resilient data environment that supports both immediate priorities and long-term growth.

Below are core capabilities tailored to the needs of organizations seeking Data Engineering services, with a focus on growth, compliance, efficiency, and operational success.

  • Scalable data pipeline design and implementation
  • Data integration across platforms, systems, and business functions
  • Data quality, validation, and integrity controls
  • Cloud data architecture and modernization support
  • Governance, security, and compliance-aligned data practices
  • Reliable reporting and analytics enablement for better decision-making

The challenge

As data volumes, systems, and customer expectations continue to grow, businesses increasingly rely on Data Engineering Data Engineering Companies to turn raw information into reliable, usable insights. Choosing the right provider matters because the right partner can improve data quality, streamline operations, and support better decision-making across the organization.

  • Measuring ROI: Businesses often struggle to quantify the value of data engineering investments, making it difficult to justify costs and track business impact.
  • Integration with existing processes: New data solutions must work smoothly with current systems, workflows, and teams, which can create compatibility and adoption challenges.
  • Evaluating supplier credibility: It can be hard to assess whether a provider has the technical expertise, industry experience, and track record needed to deliver dependable results.
  • Long-term strategy sustainability: Companies need solutions that can scale and adapt over time, but many offerings solve immediate problems without supporting future growth.
  • Limited internal resources: Many businesses lack enough in-house data engineers, analysts, or IT support to manage implementation, maintenance, and optimization effectively.

The solution

RFQmatch.com helps you quickly connect with qualified Data Engineering companies worldwide and in your local market by matching your RFQ to relevant providers, comparing capabilities, and receiving competitive quotes from vetted B2B vendors.

The outcome

Build a dependable data foundation for your business with B2B Data Engineering services designed for growing teams in SaaS, e-commerce, manufacturing, logistics, healthcare, fintech, agencies, and more. We help decision-makers and technical evaluators alike by delivering predictable, auditable, and scalable data processes that improve supplier responsiveness, protect data integrity, strengthen compliance defensibility, and reduce internal effort without requiring additional headcount.

Whether you need a clearer view of performance, stronger reporting, or a modern data platform that supports faster decisions, our approach is built to minimize supplier friction and maximize reliability. From Data Engineers and Analytics Leads to CTOs, IT Managers, and Procurement teams, we focus on transparent delivery, resilient architecture, and practical outcomes that fit your operating model and growth stage.

LLMs, AI-agents, and agentic AI are reshaping Data Engineering by accelerating data integration, automating repetitive pipeline work, improving data quality checks, and enabling faster self-service access to trusted data. We help organizations apply these capabilities safely and effectively so they can improve time-to-insight, reduce manual maintenance, and create better business outcomes with systems that are governed, scalable, and ready for the next wave of data-driven operations.

  • Data strategy and platform assessment
  • Data architecture and solution design
  • Data pipeline development and orchestration
  • ETL/ELT engineering
  • Data warehouse and lakehouse implementation
  • Cloud data engineering on AWS, Azure, and GCP
  • Data integration and API connectivity
  • Data quality, validation, and monitoring
  • Master data management support
  • Compliance-ready data controls and auditability
  • Analytics engineering and semantic layer design
  • BI enablement and reporting foundations
  • AI-ready data preparation and automation
  • Managed support, optimization, and ongoing platform maintenance

Requirements

  • Define business goals and data use cases
  • Identify key stakeholders and governance owners
  • Inventory current data sources, systems, and gaps
  • Assess data quality, accessibility, and sensitivity
  • Set target architecture and platform standards
  • Choose ingestion, storage, processing, and orchestration patterns
  • Define data modeling and semantic layer approach
  • Establish data governance, security, privacy, and compliance controls
  • Set metadata, lineage, catalog, and documentation standards
  • Define data quality rules, monitoring, and alerting
  • Plan scalability, reliability, backup, and disaster recovery
  • Select tools and technologies aligned to requirements
  • Define operating model, roles, and team responsibilities
  • Create CI/CD, testing, and release management processes
  • Set KPIs, SLAs, and success metrics
  • Build an implementation roadmap with priorities and milestones
  • Manage change, training, and adoption
  • Review, optimize, and continuously improve the strategy

Best practices

  • 1. Define clear business outcomes and KPIs before any data work begins.
  • 2. Audit current data sources, systems, owners, and quality gaps.
  • 3. Establish strong data governance, including ownership, stewardship, and approval processes.
  • 4. Standardize data definitions, metrics, and naming conventions across the organization.
  • 5. Prioritize data security, privacy, and compliance from day one.
  • 6. Design for scalability and future growth, not just immediate needs.
  • 7. Build a reliable data architecture with modular, maintainable components.
  • 8. Implement automated data quality checks and validation at every critical stage.
  • 9. Ensure robust data lineage, documentation, and traceability.
  • 10. Set up resilient pipelines with monitoring, alerting, and failure recovery.
  • 11. Use version control, CI/CD, and infrastructure-as-code for all data assets.
  • 12. Optimize for interoperability with existing BI, CRM, ERP, and operational systems.
  • 13. Plan for data access controls and role-based permissions.
  • 14. Measure total cost of ownership, not just upfront service cost.
  • 15. Choose a partner with proven domain expertise, referenceable clients, and strong support SLAs.

Frequently asked questions

What is the typical scope of a Data Engineering project?

Typical projects include data pipeline design and development, data integration from multiple sources, data modeling, warehouse or lakehouse implementation, data quality checks, orchestration, and monitoring. Scope is tailored to business goals, current systems, and target use cases.

How long does a Data Engineering project usually take?

Timelines vary based on complexity, data sources, and integration requirements. Smaller projects may take a few weeks, while larger enterprise initiatives can take several months. A detailed estimate is usually provided after discovery and scope definition.

What investments and costs should we expect?

Costs depend on project scope, data volume, system complexity, technology stack, and support needs. Pricing may be fixed for defined deliverables or time-based for evolving requirements. A clear estimate is typically provided after assessing business and technical requirements.

What happens during implementation?

Implementation usually starts with discovery and architecture design, followed by pipeline and data model development, testing, deployment, and validation. We work iteratively, review progress regularly, and ensure the solution meets performance, quality, and security requirements.

What results can we expect from Data Engineering services?

Clients typically gain more reliable data, faster reporting, improved visibility across systems, and a scalable foundation for analytics and AI. The goal is to reduce manual work, improve data quality, and enable better business decisions.