Senior data architecture consulting for New York City and the tri-state area. Former Microsoft data architects delivering enterprise data architecture design, cloud data engineering, and AI-ready data infrastructure to New York's most data-intensive organisations.
Data Architecture Consulting — New York
New York City's financial services, media, and healthcare sectors generate some of the most demanding data architecture challenges in the world. The scale, complexity, and regulatory requirements of enterprise data environments in New York — BCBS 239 for trading data, HIPAA for patient records, SEC reporting requirements for investment firms — require a level of architectural rigour that generic IT consulting firms cannot deliver.
Our team of former Microsoft data architects brings that rigour to New York clients. We have designed data systems at enterprise scale, inside organisations where the cost of a poorly architected data pipeline is measured in regulatory fines, not just engineering hours. That experience transfers directly to every engagement we run.
We work across financial services, healthcare, media, technology, and retail — and understand the specific data and analytics demands these sectors place on their infrastructure. Whether you need a full data architecture assessment, a cloud data platform build, or senior architectural oversight of an internal team, we have delivered it at comparable scale.
Engagements can be structured as fixed-price projects, time-and-materials, or ongoing monthly retainers. We scope clearly, price honestly, and deliver on what we commit to. Assessments typically take two to three weeks and produce a prioritised roadmap. Full platform builds run eight weeks to six months depending on scope.
Why DataArchitect.co
Industry Experience
Investment banks, hedge funds, and private equity firms face some of the most demanding data governance requirements in any industry. BCBS 239 compliance, risk data aggregation, trading data lineage, and real-time reporting demands require data architectures that most firms have not yet built. We have designed data platforms for financial services organisations where the cost of a wrong architectural decision is regulatory, not just operational.
New York healthcare systems — hospital networks, health insurers, and pharma organisations — operate in a highly regulated data environment. HIPAA, 21 CFR Part 11, and interoperability requirements under HL7 FHIR shape every architectural decision. We design healthcare data architectures that are compliant by design, not compliance-patched after the fact.
New York is home to major media organisations whose data architecture challenges centre on audience analytics, content performance, and advertising attribution — often across fragmented data environments built over decades of acquisitions. We have modernised data stacks for media organisations moving from legacy on-premise systems to cloud-native lakehouse architectures.
Technology companies in New York — whether established enterprises or scaling startups — often have the opposite problem from legacy industries: they have too many data tools and not enough architectural coherence. We design the governance layer and the data model that makes a proliferation of data tools into a coherent, trustworthy system.
Law firms, management consultancies, and accounting firms in New York are increasingly expected to use data to drive client outcomes and internal operations. We design data architectures for professional services firms that are appropriately scaled — enterprise-rigorous without enterprise-bureaucratic overhead.
Insurance carriers in New York operate with data models of extraordinary complexity — actuarial tables, policy data, claims data, reinsurance structures. We have designed data architectures for carriers modernising away from mainframe-era data environments into cloud platforms capable of supporting advanced analytics and AI.
What We Deliver
A structured review of your current data infrastructure — warehouse design, pipeline reliability, governance gaps, data quality issues, and architectural debt. Delivered in two to three weeks. Output: a prioritised remediation roadmap with effort and cost estimates for each item.
End-to-end design and implementation of a modern cloud data platform on Azure, Databricks, or Snowflake. Includes medallion architecture design, ingestion pipeline development, semantic layer build, and access control framework. Eight to twenty weeks depending on scope.
Migration from legacy on-premise systems (SQL Server, Teradata, Oracle) to a cloud-native lakehouse. We design the target architecture, build the migration pipelines, run parallel operations, and cut over cleanly — without disrupting your business during the transition.
Most AI projects stall because the data underneath them is not ready. We design the streaming pipelines, semantic layers, real-time quality controls, and feature stores that AI and agentic use cases require — building the infrastructure layer before it becomes a blocker.
Canonical metric definitions, data product ownership frameworks, lineage tracking, and certified semantic layers. The governance infrastructure that makes your data trustworthy enough that every team — including AI systems — can rely on it.
Senior architectural leadership on a monthly retainer. We attend design reviews, make platform decisions, review engineering work, and provide executive-level guidance — without the cost and commitment of a full-time Principal Data Architect hire in the New York market.
FAQ
Free 30-minute discovery call. No pitch — just an honest assessment of where your data architecture is costing you and what to do about it.
Book a Discovery Call →