Selected Work

AI agents, enterprise data platforms, warehouse optimization, and AI enablement

I help enterprise teams ship AI agents, de-risk data-platform migrations, cut warehouse cost, and lead AI adoption — with proof, not slides.

Problems I solve

AI engineering & agentic systems — Coding agents wired to your data platform, CLIs, and real schemas: Text-to-SQL, tool/API contracts, evals, run manifests, sandboxed execution. Agents that ship to production, not chat demos.

Migration assurance — Automated cross-platform validation for Databricks/Snowflake and cloud moves: schema, row-count, key-distribution, and date-range checks across dozens of tables — in a dashboard the team trusts.

Warehouse cost & performance — Profile the real bottleneck, benchmark across data scales and warehouse sizes, and prove row-level correctness before rollout. Faster and still right.

AI enablement & change — Opportunity discovery, stakeholder alignment, PoC-to-production, and capability building — with governance and ROI, not hype. Led a DS/analytics team and an ~11M SEK Vinnova/EU portfolio.

Time series & telemetry ML — Production ML for sensor and telemetry data — activity recognition, anomaly detection, forecasting — fast enough for edge/IoT (ROCKET family) at state-of-the-art accuracy.

How I work

Advisory — A few sessions to scope, review architecture, or pressure-test a plan.

Embedded principal / interim lead — Weeks to months on your team; I own deliverables and ship alongside your people.

Hands-on implementation — I build the thing and write the code, not slide decks.

Evaluation-first delivery — A clear success criterion up front: I prove correctness before I optimize, and show evidence before I ship.

Selected examples

SQL Pipeline Optimization

Redesigned a critical daily full-recompute pipeline into a validated incremental one — 5-10x faster with 50%+ compute savings and row-level correctness proof. Multi-scale benchmarks and parallel AI-agent workflows killed an attractive but broken optimization before it reached production.

Read the case study

Cross-Platform Migration Validation

Built a production-grade validation system for a large Databricks-to-Snowflake migration: automated comparison across dozens of tables, historical result storage, and a live team dashboard — from zero to deployed in about a week using a coding agent.

Read the full case study

Code Migration Methodology

Developed a practitioner’s framework for large code migrations and clean-room-style rewrites with coding agents. Covers evidence-preservation, behavioral oracles, shortcut audits, and agent guardrails — drawn from multiple 10k+ line migrations.

Read the essay

Time Series Classification for Production

Delivered a time series classification system for industrial telemetry with state-of-the-art accuracy and 10-100x faster inference than deep learning baselines. Designed for edge and IoT deployment where latency and power matter.

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Engagement fit

You should reach out if:

  • You are a data platform or data engineering leader dealing with a migration, cost problem, or analytics modernization.
  • You are driving AI adoption and need someone to run discovery, align stakeholders, and take PoCs to production — not just advise.
  • You are a technical sponsor or architect who needs a senior practitioner to lead or unblock a workstream.
  • You need an interim team lead who can own a roadmap, manage stakeholders, and still write code.
  • You have a time series or telemetry problem that needs production ML, not a research paper.

I typically work with enterprise teams in manufacturing, logistics, energy, and industrial IoT — but the methods transfer.