Data infrastructure and analytics
for financial services.
Data Lowdown helps financial services firms build reliable, scalable data platforms. We work hands-on with your team to design, build, and manage the infrastructure behind better decisions. From pipeline development to cloud migration to reporting, we handle the full data lifecycle so your team can focus on what the data tells you — not how to get it.
Working systems, not slide decks.
We build systems that work — not decks that present well. Our focus is working infrastructure: reliable pipelines, clean data, and architecture that scales without needing to be rebuilt every eighteen months.
We don't sell a platform. We design, build, test, and deploy, and we stay until what we've built is running in production and your team can operate it independently.
What we do.
Four areas we work across — from raw sources through to production analytics.
Data Engineering
End-to-end pipeline development, from ingestion to transformation. We build data infrastructure that handles the complexity of financial data — multiple custodians, fund administrators, market data vendors, and internal systems all feeding into a single analytical layer. Our pipelines are designed for reliability first: automated monitoring, clear error handling, and documentation your team can actually follow.
Cloud Infrastructure
Architecture, migration, and management across GCP, Azure, and AWS. Infrastructure-as-code, containerized deployments, and CI/CD best practices for production data workloads. We help firms move off legacy on-prem systems without disrupting day-to-day operations, and we build environments that your team can manage independently after handoff.
Analytics & Reporting
Reporting and analytics platforms that give investment, operations, and compliance teams reliable access to the data they need. Dashboards, semantic layers, and automated reporting workflows that replace ad hoc requests and manual spreadsheet processes. We build for self-serve — the goal is to reduce your team's dependency on us, not increase it.
AI & Intelligent Data Products
Applied AI and LLM-powered solutions built on top of your existing data infrastructure. We design and deploy retrieval-augmented generation (RAG) systems, document intelligence pipelines, and classification models that turn unstructured data — memos, filings, reports, contracts — into structured, queryable assets. Every solution is built to run in production, integrate with the systems you already operate, and solve a specific business problem.
A few recent outcomes.
Reduced ETL processing time for a North American asset manager.
Manual processing time eliminated from monthly close and investor reporting at an asset management firm.
Dashboards migrated to a modern cloud analytics platform for a national retailer — zero downtime.
Who we work with.
We work primarily with mid-market financial services firms — asset managers, insurance carriers, banks, and family offices — that have outgrown spreadsheets and manual processes but aren't ready to build a full internal data engineering team. Our typical client has a small but capable technology or operations team and a growing need for reliable data infrastructure to support investment decisions, regulatory reporting, and client communications.
We also work with enterprise retail organizations on scoped data engineering and migration projects — modernizing legacy reporting systems, consolidating data platforms, and building analytics infrastructure that supports cross-functional teams at scale.
- Asset Management
- Banking
- Insurance
- Capital Markets
- Retail
- Family Office