Mercadona Tech
Public posts on bringing analytics in-house with a Snowflake + Airflow stack
Spanish peer, similar surface area — useful reference for what a small-team-owns-the-platform posture looks like in writing.
Source: mercadonatech.com
Lumeo Data ↗ site
Senior Data Platform Engineer — Remote (Spain)
Your eng blog flagged pipeline reliability as the 2026 wedge — same move I made at a fintech SaaS, daily failures to near-zero.
What I read about you
Lumeo Data — five things I noticed before writing this.
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The Senior Data Platform JD says 'reduce incidents by 80%' as 2026 OKR — exact same outcome I shipped at a fintech SaaS.
Source: careers
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Engineering blog mentioned a Redshift→Snowflake migration is on the roadmap — I led the same migration end-to-end in 2024.
Source: engineering blog
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Public talks describe a 2-3 person data team owning a large surface — that's the team shape I've already operated as de facto tech lead.
Source: talk video
The threat nobody is pricing in
Is your company ready to compete with the 1-person companies that will emerge in the next 12 months?
In the next 12 months, a single engineer with the right agent stack will out-iterate most product teams. The companies that survive aren't the biggest — they're the ones whose know-how is documented (so it can be reshaped at speed) and whose infrastructure is agent-ready (so pivots take days, not quarters). I help you build both quietly, in parallel with the shipping you already have to do — that's the differentiator most candidates won't even name.
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Document the know-how
Agent-driven processes that capture decisions, runbooks, and tribal knowledge as they happen — not a quarterly Confluence audit.
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Make infra agent-ready
MCP servers + composable internal tools so when the next pivot lands, the agent loop is one prompt away, not one rebuild.
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In parallel with shipping
Both happen alongside the roadmap you already have. No 6-month transformation programme; the artefacts compound from week one.
Who's already moving this way in your space
Three peer-tier teams have published on the same reliability shape.
Your engineering blog flagged 80% incident reduction as the 2026 OKR. Below: three peer-tier teams that have published on the same problem shape. Useful reference points, not benchmarks.
Glovo
Engineering blog covers agent-assisted on-call and incident-triage workflows
Same headcount class — adjacent to the OKR you've published. Worth reading for the operational shape, not the exact numbers.
Source: medium.com/glovo-engineering
Cabify
Public engineering writing on consolidating warehouse + dbt + Airflow ownership
Adjacent to the migration on your roadmap — the recurring lesson in their posts is that one owner across the vertical is what makes the timeline land.
Source: medium.com/cabify-product
I've worked on both shapes in past roles — happy to walk through what carries over and what is target-specific.
What I'd do in your first ~90 days
Concrete, not aspirational.
First wedge would be wiring the reliability work — IaC for the Airflow + Snowflake stack, ArgoCD for the EKS workloads, and a dbt CI gate that blocks the pipeline failures the JD names. I shipped this exact pattern at a fintech SaaS. The second move is the migration: Redshift → Snowflake is on your roadmap and I led the same one in 2024 end-to-end (architecture, execution, cutover). The third move is the easy win nobody plans for — stand up Langfuse-style tracing across the model calls you already have so the next quarter's roadmap is defended with data, not vibes.
Why speed-to-prod is the wedge
Companies shipping agentic features in weeks are not the ones with bigger teams.
The teams that hit the 80% incident-reduction OKR are not the ones that hire two more engineers — they hire one who can own the full vertical (infra → ingestion → warehouse → dbt → observability) and ship the IaC + GitOps that makes it durable. I've shipped this pattern more than once.
- near-zero incidents at fintech SaaS
- 1 dev owns full data vertical
- 20+ data sources owned
Closest match in my portfolio
This one's been shipped — to a stack that overlaps yours.
Greenfield data platform — European e-commerce retailer
Same instinct your roadmap implies: pull analytics off the legacy bottleneck before it's the thing that paged someone at 3am.
Designed and built the company-wide big data infrastructure from scratch. Decoupled analytics from a 20-year-old production Oracle DB; eliminated availability risk and slashed costs.
- Python
- AWS
- Docker
- Kubernetes
- FluxCD
- Argo
- Vue.js
11+
Years engineering
30+
Self-hosted services
20+
Data sources owned
2
Nodes, zero touch
One short call this week.
If after a 15-minute call it isn't the right fit, no pressure — and you keep the analysis I already wrote.
Fidel Perez · Senior Data Engineer · AI-First · 11+ yrs