Build, migrate, and operate the data platform your business needs for analytics and AI workflows.
Preferred Partner
Partner Network
Elite Partner
Data engineering services build the pipelines and platforms that turn raw data into something teams, analytics tools, and AI models can use. phData delivers this across four services — intelligence platform architecture, AI-ready data foundations, data migrations, and agentic data engineering enablement — accelerated by phData Forge, our AI-native delivery system.
Intelligence Platform architecture
AI-ready data foundations
Data migrations
Agentic data engineering enablement
Enterprises bring phData in when data is siloed or AI initiatives are blocked on unreliable pipelines. With an ever-growing catalog of agents and skills, our engineers use phData Forge build and extend on every project. Each client benefits from hundreds of prior engagements from day one. Whether it’s migrating a legacy warehouse or grounding AI in a governed semantic layer, our expertise and tooling help you move faster with less risk.
Our engineers specialize in Intelligence Platform architecture, data migrations, semantic modeling, and agentic workflows built on a governed data foundation.
We design the data foundation layer of your Intelligence Platform, the architecture and ingestion standards every use case depends on. Authentication, security, networking, and observability are built in from day one, so the platform scales without re-engineering.
We build the pipelines, models, semantic layers, and integrations behind your AI-ready data foundation. Quality testing, governance, and shared business definitions are enabled from the start, so the foundation gets more reliable with every new source.
We migrate legacy environments — Teradata, Oracle, Informatica, Hadoop, and similar systems — to Snowflake and other modern targets. Forge’s SQL Migration Agent handles translation and validation at scale, so our engineers focus on the judgment calls, completing migrations faster and with less risk.
We work alongside your engineers to build the skills, workflows, and Forge-native capabilities they need to operate as Agentic Data Engineers with purpose-built agents plus the hands-on coaching that makes it stick.
Data engineering builds the governed layer that connects data, AI, and business decisions into production. See how that layer supports analytics, GenAI, and agents, and why a well-modeled data foundation is the prerequisite AI can’t skip.
Onboard data from internal and external sources at any latency, whether batch, streaming, or real-time.
Migrate legacy systems and workloads to modern cloud platforms using Forge agents and skills.
Establish lineage, quality standards, and governance from the point of entry so the foundation is trustworthy from day one.
Build data models, semantic layers, and data products that give every consumer a shared, consistent understanding of the business.
Enforce data quality and data contracts so every pipeline ships with explicit expectations rather than discovering problems downstream.
Accelerate model scaffolding, test generation, and documentation with Forge agents and skills.
Serve trusted data to analytics tools, AI applications, and agentic workflows across the organization.
Activate the intelligence the platform was built to produce, from self-service reporting to production AI agents operating at scale.
Maintain the catalog of data products, semantic definitions, and lineage to keep the platform trustworthy as it grows.
Discover how phData helped a major regional bank plan a move to Snowflake and then executed that plan with a successful migration to the cloud.
Learn how KNIME flow variables work, when to use them, and best practices from phData engineers who’ve applied them on real client projects.
Learn how phData's two new agentic commands (discovery and pipeline-build) turn a data contract into validated code, tests, and mock data through agentic automation.
Data engineering is the practice of building the pipelines, models, and platforms that collect, clean, and deliver data so it can be used for analytics, machine learning, and AI. It covers everything from ingesting raw data to modeling it for business use to monitoring pipelines in production.
phData has deep experience across all major cloud providers, with specialized expertise in Snowflake, AWS, dbt, and Anthropic, plus legacy environments including Teradata, Oracle, Informatica, MS-SQL, Netezza, and Hadoop. Our engineers bring a viewpoint from thousands of data projects, with clear best practices for each technology.
Architecture and design are often part of a data engineering engagement, but for large or complex projects, phData recommends a dedicated data strategy engagement first, one that defines the architecture before execution begins.
phData Forge is our AI-native delivery system. Agents handle drafting and verification across multiple steps in parallel, while our consultants own the quality gates, architectural decisions, and production readiness, with faster outcomes but without cutting corners.
phData offers four core data engineering services: intelligence platform architecture, AI-ready data foundations, data migrations, and agentic data engineering enablement, each delivered by engineers who specialize in a specific part of the stack, accelerated by Forge's agents and skills.
Learn how phData can help solve your data engineering challenges:
