Data Warehouse Modernization
Modernize legacy EDW infrastructure through cloud data warehousing, ETL/ELT pipeline optimization, and multi-cloud deployments on Snowflake, Databricks, and Azure — with built-in performance optimization and governance.
Modern enterprises generate more data than legacy systems can handle. Cybic's Cloud Data Warehouse Engineering Services help you consolidate, transform, and scale your data infrastructure on platforms like Snowflake, Databricks, and Azure — enabling real-time analytics, AI-readiness, and governed data access across every layer of your organization.
End-to-end data warehouse engineering across cloud platforms — from modernization and pipelines to governance and real-time analytics.
Modernize legacy EDW infrastructure through cloud data warehousing, ETL/ELT pipeline optimization, and multi-cloud deployments on Snowflake, Databricks, and Azure — with built-in performance optimization and governance.
Design and optimize high-performance ETL/ELT pipelines for real-time data ingestion, transformation, and loading — enabling low-latency, AI-ready data flow across cloud and hybrid environments.
Conduct data landscape audits and build governance frameworks with GDPR, HIPAA, and CCPA compliance — defining data ownership, policy structures, and strategic roadmaps aligned with business objectives.
Design infrastructure-agnostic, cloud and hybrid architectures with RBAC, encrypted data protection, and audit trails — built to scale across AWS, Azure, and Google Cloud while meeting SOC 2 and ISO standards.
Build AI-enabled dashboards and self-service BI solutions using Tableau, Power BI, and Looker Studio — delivering real-time KPI tracking, predictive analytics, and prescriptive reporting for enterprise decision-making.
Advise on enterprise data strategy, cloud platform selection, and integration modernization — delivering structured roadmaps that address siloed data and align infrastructure with AI and analytics readiness.
We audit your existing data infrastructure — mapping data sources, siloed systems, legacy EDW components, and integration gaps — to build a clear picture of your current state and define measurable modernization objectives.
See how Cybic has helped enterprises modernize their data infrastructure and unlock real business value.
Cybic combines engineering-led execution with deep data platform expertise to deliver cloud data warehouse solutions that are production-ready, governed, and built for scale.
Projects are driven by experienced engineers who architect, build, and integrate directly — eliminating translation gaps between design and deployment.
Security, RBAC, auditability, and regulatory alignment — including GDPR, HIPAA, and SOC 2 — are embedded at the architectural level from day one.
Solutions are designed to operate across AWS, Azure, Google Cloud, or hybrid environments without locking your organization into a single vendor ecosystem.
We combine data infrastructure, automation logic, and AI models into unified systems — ensuring your warehouse is immediately AI-ready for analytics and ML workloads.
A specialized engineering team focused on cloud data infrastructure and enterprise AI.
Cybic is an AI and data engineering company purpose-built to help enterprises transform their data infrastructure into operational intelligence. With deep expertise across Snowflake, Databricks, AWS, Azure, and Google Cloud, Cybic's engineers have delivered cloud data warehouse solutions for organizations in Oil & Gas, Healthcare, Manufacturing, Retail, and the Public Sector. Every engagement is structured around real implementation — not advisory decks — with governance, security, and scalability embedded from the first line of architecture. Cybic's work with global technology partners including NVIDIA, Google, Microsoft Azure, and Databricks reflects a commitment to engineering that meets the highest standards of enterprise performance and compliance.
A data warehouse engineer designs, builds, and maintains the systems that store and organize large volumes of enterprise data for analytics. This includes architecting cloud warehouse platforms like Snowflake or Databricks, engineering ETL/ELT pipelines, optimizing query performance, implementing data governance controls, and ensuring the infrastructure scales reliably to support business intelligence and AI workloads.
Talk to a Cybic data warehouse engineer for a tailored assessment of your environment.
Recognized engineering expertise on the Snowflake data cloud platform.
Validated delivery capability on Databricks lakehouse architecture.
Data security practices aligned with international information security standards.
Tell us about your data infrastructure challenges and we'll connect you with a Cybic engineer to scope a solution tailored to your environment, compliance requirements, and analytics goals.