Production-grade data platforms, shipped in weeks
Data Platform Engineer building modern stacks that scale without breaking production
I build data platforms that let businesses move fast without breaking production — multi-tenant ingestion, semantic layers, and FinOps-tuned warehouses, delivered in weeks via AI-assisted engineering.
- Is your warehouse spend climbing faster than your data volume?
- Are tenant or source-system additions a multi-week engineering project?
- Do executives still wait days for numbers your teams disagree on?
- Are pipelines fragile, undocumented, and missing tests or contracts?
- Need to migrate to open table formats, Iceberg, or a governed semantic layer — without stalling the business?
I deliver end-to-end platforms — Snowflake, dbt, Dagster, Terraform, AI-assisted — in single-week increments, not multi-month programmes.
About me
I'm Vadims, a Data Platform Engineer based in the UK. Over the past decade I've gone from analyst to platform engineer — designing, building, and operating the full modern data stack across fintech, manufacturing, and B2B SaaS. My work sits at the intersection of infrastructure and business outcomes: warehouse architecture, multi-tenant ingestion, cost optimisation, semantic layers, data contracts, and self-service analytics that executives and operators actually trust.
I now use AI-assisted development and context engineering to compress what used to be multi-month platform builds into single-week deliveries — without sacrificing quality, governance, or consistency.
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Proven Results
90–99% lower ingestion & warehouse cost
80% faster time-to-insight delivery
99.9% platform uptime in production -
Industry Experience
Fintech | Manufacturing | B2B SaaS
Multi-tenant, multi-billion-row platforms at scale
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Technology Stack
Snowflake | AWS | Python | :simple-dbt: dbt | :simple-dagster: Dagster | Terraform | :simple-apacheiceberg: Iceberg
With extensive experience designing and operating end-to-end data platforms, I've architected multi-tenant CDC ingestion at the scale of thousands of tenant schemas, governed semantic layers backed by data contracts, real-time anomaly detection, and Iceberg-based open-table-format migrations. My clients unlock deep, trustworthy insights, materially reduce platform cost, and accelerate decision-making — without trading off reliability.
Why work with me?
Here's what sets me apart and how I can help drive value for your business:
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FinOps & Cost-Efficient Scale
I've cut warehouse and ingestion spend by 50–99% through warehouse tuning, query optimisation, and selective migrations to Apache Iceberg with Polaris catalog — while still hitting sub-minute rebuilds on multi-billion-row fact tables.
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Reliability via Contracts & TDD
Every pipeline I ship enforces data contracts across a data-mesh boundary and follows test-driven development with CI/CD in containers. The result: protected consumption layers, 99.9% platform uptime, and zero-regression releases.
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Semantic Layer & Self-Service
I deploy Snowflake-backed semantic layers with documentation-backed metric definitions and self-serve BI. Ad-hoc definition requests typically drop ~90%, executives stop arguing about whose number is right, and operators get insight in minutes.
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AI-Accelerated Delivery
Using Cursor, context engineering, and skills-based agents, I compress what used to be multi-month platform builds into single-week deliveries — with consistent, predictable, governed outputs. You get production quality at startup speed.
Featured Case Study
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Multi-Tenant Ingestion at Scale: 90% Cheaper, 80% Faster, 99.9% Uptime
90–99% cost reduction | 80% latency reduction | 99.9% uptime
Tech Stack: AWS DMS | :simple-amazonsqs: SQS | :simple-awslambda: Lambda | Snowpipe | :simple-apacheiceberg: Iceberg + Polaris | :simple-dbt: dbt
How a multi-tenant SaaS platform with ~2,000 PostgreSQL tenant schemas re-architected ingestion across DMS, SQS, Lambda, and Snowpipe — then cut Snowflake ingestion cost by 99% by migrating to Apache Iceberg with Polaris catalog.
Frequently asked questions
How quickly can you start working on my project?
Typically, I can kick off new projects within 1-2 weeks after contract finalization. For urgent or high-priority situations, I keep some flexibility in my schedule—just let me know your timeline during our initial consultation, and I'll do my best to accommodate.
Do you require a minimum project size or commitment?
While I'm flexible on project sizes, engagements of around 20 hours or more typically allow for deeper analysis, tailored solutions, and measurable impact. However, we can certainly start with a smaller pilot project to ensure mutual fit and immediate value.
What industries do you have experience in?
I've delivered platform engagements across fintech, manufacturing, and B2B SaaS, including multi-tenant SaaS ingestion at scale, analytics engineering, governed semantic layers, real-time anomaly detection, and FinOps / open-table-format migrations.
How do you handle data security and confidentiality?
Data security is at the heart of my work. I sign comprehensive NDAs before beginning any engagement, utilize enterprise-grade encryption, and strictly follow best practices aligned with SOC2 and ISO27001 standards. Additionally, I'm experienced working within existing security frameworks and compliance requirements.
What's your pricing structure?
I offer productised, fixed-scope engagements (platform builds, ingestion at scale, semantic-layer rollouts, FinOps / Iceberg migrations) priced against delivered outcomes rather than hourly time. For ongoing operation and evolution I offer retainer packages. We'll pick the model in our intro call based on scope and risk profile.
How do you communicate progress and results?
Clear and consistent communication is key—I provide weekly updates and hold regular check-in meetings. You'll receive comprehensive documentation of all findings and recommendations, complemented by interactive, self-service dashboards.
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Ready to ship a production-grade data platform?
Free 30-minute consultation
Pragmatic platform roadmap for your business
ROI, risk & realistic timeline
No pressure — just an honest second opinionLet's pressure-test your current stack, identify the highest-leverage moves, and map a delivery plan that ships value in weeks — not quarters.