Lead Data Engineer

Location: Barcelona (Hybrid) - Type: Full-time

Get to know us:

Started in 2016, Frekuent is now the all-in-one payment and loyalty platform for unattended environments - 500+ clients, 100M+ transactions a year, 2.5M+ users across Spain, France, Italy, Portugal, and Singapore. We turn one-time buyers into lifetime clients with cashless, contactless, effortless payments: less friction, more reasons to come back.

2026 has been our biggest year yet - we've hyperscaled from 40 to 100+ people, with more hires on the way, and closed a €6M funding round to fuel what's next.

And we're just getting started - our goal is to become the default payment and loyalty layer behind every unattended transaction, everywhere.

Curious? Check us out at www.frekuent.com.

Why this role exists:

Data at Frekuent isn't a side project - every tap on a Frekuent Spot, every loyalty reward, every fraud check produces it, and we're scaling fast enough that our current platform is starting to show the seams. We're hiring a Lead Data Engineer to own that platform end-to-end: not write a roadmap slide, but rebuild the pipelines, standards, and trust so the whole company - including the AI tools we're building on top of our data - can run on real numbers instead of guesses.

You'll work directly with the exec team, and they want a partner who turns ambiguous business problems into a working data platform, not just a bigger backlog.

What you'll actually do:

• Audit the current platform's weak spots and turn them into a concrete, prioritized roadmap.
• Set technical direction for data modeling, ETL/ELT, and infrastructure-as-code, and lead the engineers who build it.
• Own performance, reliability, and cost as data volume grows - not a \"set it up once\" job.
• Partner with the exec team: turn their priorities into a real plan, balance asks, and delegate across the team.
• Build real CI/CD for analytics, and set the bar for data quality, lineage, governance, and observability.
• Build the AI substrate: schema context, curated semantic layers, and safe read paths - so an assistant doesn't have to guess.
• Champion a real data culture - push our products and processes to generate clean, reliable, trustworthy data.
• Own the data team's OKRs (trust, self-service, foundations, AI enablement), mentor engineers, help hire, and bring in tools that genuinely help.

What you bring:

• 8+ years in data engineering, including 3+ in a lead or technical-direction role.
• Deep SQL and strong Python, with hands-on experience running a cloud data platform - Fabric, Snowflake, BigQuery, or Databricks (Fabric a strong plus).
• Real SQL Server experience - schema design, query tuning, CDC/replication at volume - plus strong modern-data-stack skills, dbt especially.
• Solid grip on dimensional modeling, distributed systems, and CI/CD for pipelines.
• Genuinely fluent with AI tooling - you know exactly where it helps and where it doesn't.
• Experience with high-throughput data needs; payments or transactional systems a strong plus.
• Strong written communication (decision records, dictionaries, runbooks), and able to turn fuzzy goals into trackable key results.
• Track record mentoring engineers and leading cross-functional projects, comfortable in a fast-scaling, shifting-priority environment.

Bonus points if you...

• Have worked on Azure, or hold a Microsoft certification - DP-600 or DP-203.
• Have fintech, payments, or regulated-industry experience (PCI DSS a plus), or handled IoT/connected-device telemetry at volume.
• Have built real-time/streaming pipelines (fraud detection, transaction monitoring, Event Hubs, Fabric RTI), or gone beyond Power BI reports into semantic models and row-level security.
• Have set up a data governance framework from scratch, or built an internal LLM assistant with real guardrails.

How we work:

• Fast, autonomous, low-bureaucracy.
• We measure output, not hours in a chair.
• Resilience means iterating until it works - not giving up early.

What's In It For You

• A hybrid model that works - Enjoy the energy of our office 3 days a week and the flexibility of working remotely the other 2.
• Flexible schedule - because we trust you to own your time and your outcomes.
• Meal vouchers - Enjoy a monthly support of meal vouchers to make your workdays tastier.
• Health & wellness - private health insurance and discounted gym memberships to keep both body and mind in top shape.
• Learning & development - English classes and role-specific training, because your growth is part of our journey.
• 23 days of paid time off - plus local holidays, because great ideas need space to rest.
• A dynamic, fast-growing environment - where each day