Services
Fractional Data Architect & Senior Data Engineer for startups, scaleups, and SMEs. Working 1–3 days per week with 2–4 clients at a time, to design, build, and evolve data platforms that are reliable, cost‑aware, and aligned with the business.
| Service | Best for | Duration |
|---|---|---|
| Fractional Data Architect | Ongoing senior leadership | 2–3 days/week, 6–12 months |
| Architecture Advisory | Specific decisions | Hours to days |
| Platform Review | “Is our stack broken?” | 10 days |
| Team Alignment Sprint | Ownership conflicts | 4–6 weeks |
| Hiring & Team Support | Scaling the team | 1 day/week, 2–4 months |
1. Fractional Data Architect & Senior Data Engineer
For: Scaleups that need senior data architecture and engineering leadership, but aren’t ready for a full‑time Head of Data.
What this is
An embedded fractional data architect / senior data engineer who:
- Owns the overall data architecture and technical direction.
- Guides platform decisions (warehouse, lakehouse, dbt, orchestration, observability).
- Works directly with your engineers to make changes real, not just theoretical.
- Aligns data, product, and ops on priorities, ownership, and ways of working.
Typical outcomes
- Fewer outages, fewer “mystery” pipeline failures.
- Clear technical roadmap for the next 6–12 months.
- Data platform that actually supports new use cases instead of blocking them.
Engagement
- 2–3 days per week
- 6–12 months
Why this duration: Architecture and delivery momentum take a few months to show measurable stability and cost impact.
📅 Discuss a Fractional Engagement
2. Architecture Advisory
For: Teams facing a specific architecture question or decision—migration, tool selection, cost optimization, or a second opinion on a proposed design.
What this is
Focused, on-demand advisory for open questions:
- One-off deep dives into a specific problem or decision.
- Review of a proposed architecture, vendor choice, or migration plan.
- Sounding board for your internal architects or engineers.
Typical outcomes
- Clear recommendation with trade-offs explained.
- Confidence to move forward (or to change direction).
- Knowledge transfer to your team.
Engagement
- Flexible: a few hours to a few days, depending on scope.
Why this duration: Most decisions only need a fast, senior deep-dive and a clear recommendation.
📅 Discuss Architecture Advisory
3. Platform Review
For: Companies that feel their current data stack is “fragile, slow, or too expensive” and want a structured, outside assessment.
What this is
A fixed 10-day engagement to review your data platform end-to-end:
- Current‑state assessment: pipelines, models, storage, governance.
- Risks and bottlenecks: reliability, scalability, cost, and team workflows.
- Future‑state architecture: pragmatic patterns, not vendor slides.
- 90‑day action plan: what to fix now, what to postpone, and what to ignore.
Typical outcomes
- Clear picture of technical debt and its impact.
- Prioritized backlog that your team can act on.
- Shared language between tech and business about “what good looks like.”
Engagement
- 10 days (structured engagement)
Why this duration: Ten focused days is enough to audit end-to-end, validate risks, and produce a 90-day action plan.
4. Team Alignment Sprint
For: Organizations where data, product, and ops teams all depend on the platform, but don’t agree on ownership or priorities.
What this is
An intensive sprint focused on how people work around the data platform, not just the technology:
- Stakeholder interviews to map expectations, pain points, and responsibilities.
- Workshops to clarify ownership (who owns what, where handoffs happen).
- Definition of SLAs, rituals, and decision rules around data work.
- 30/60/90‑day plan to embed the new ways of working.
Typical outcomes
- Fewer “drive‑by” requests and urgent escalations.
- Clearer responsibilities between data, product, and ops.
- Teams that can ship changes without stepping on each other.
Engagement
- 4–6 weeks (intensive), usually 2–3 days per week during the sprint.
Why this duration: Alignment needs interviews + workshops + a short adoption window to make new ownership stick.
📅 Discuss a Team Alignment Sprint
5. Hiring & Team Support
For: Companies hiring their first data people or growing from 1–2 to 5+ data engineers.
What this is
Hands‑on support to build the right team around your platform:
- Clarify what you actually need: data engineer vs analytics engineer vs architect vs head of data.
- Help write role descriptions that attract the right profiles.
- Participate in interviews and technical assessments.
- Design onboarding so new hires can be effective in your stack and context.
Typical outcomes
- Fewer mis‑hires and shorter time‑to‑effectiveness.
- Roles and responsibilities that match the reality of your platform.
- A team that can maintain and evolve the architecture, not just patch it.
Engagement
- 1 day per week over 2–4 months (can be combined with other services).
Why this duration: Recruiting and onboarding cycles typically need 2–4 months to see hires become productive.
📅 Discuss Hiring & Team Support
How a Fractional Engagement Works
- We start with a short call to understand your context and what’s hurting most.
- If there’s a fit, we agree on a clear scope, days per week, and initial 6–12 week focus.
- You get senior‑level architecture and engineering support, without the cost and commitment of a full‑time leadership hire.
📅 Schedule a 30‑minute call to see which of these is the right starting point for your situation.