Senior Data Engineer - Data Platform team (100% Remote within Spain)

Welcome to the good side of tech 👋

You might have heard about us, but with a different name: Doctoralia. It all started 12 years ago when we asked ourselves: is anyone in healthcare thinking about patients? We jumped in and we empowered patients by giving them access to leave and read reviews about their visit.

We then provided doctors with the technology to manage bookings easily and save time, so they could devote themselves to what they always wanted: treating patients. And today is the day in which we ask you: wanna join us in the next step of making the healthcare experience more human?

Docplanner at scale

We are leaders in 13 countries so far, and more than 90 million patients trust us every month. 300k+ specialists believe in us and our product, and so do leading venture capital funds such as Point Nine Capital, Goldman Sachs Asset Management and One Peak Partners. And yet, employing over 2.500 people all over the globe, we managed to keep the startup mindset we started with over 10 years ago.

At Docplanner, we are a diverse group of over 300 people working in Engineering, Data, and Product teams. We are responsible for building the product for all locations. Many of us have been here for over 5 years, yet we still welcome each new person with great joy and excitement.

We could tell you about us, but we will let our reviews on Glassdoor speak for themselves. In case you’d like to see how it feels to be 100% yourself at work, here’s a video of us .

And why should you join us?

Because it feels good to tell your family and your friends how you made the world a little bit better. You go to bed knowing that what you do matters, and that your talents align with your beliefs.

We want to make the healthcare experience more human, and that starts with you being you. We believe that taking the diversity of human experience into account makes a better healthcare experience for all. We’re not just different: we embrace diversity. We will encourage you to come to work your whole self, and that includes not coming to the office at all if you prefer not to, as we're 100% remote-friendly.

Job Description

At Docplanner , data is at the core of everything we do to make the healthcare experience more humane. Our Data Platform Team is the backbone for all things data: serving analysts, engineers, and product teams with robust infrastructure, high-quality data pipelines, and modern tooling.

We’re looking for a Senior Data Engineer to join our team and support our growing platform operations. This is a role for someone who has already built and operated data platforms at scale, has strong opinions (loosely held) about how they should work, and wants to own problems end to end rather than tickets.

What this role is really about

You'll be a technical reference point in the team: designing and building the systems that ingest, transform, and serve data for the whole company — and raising the bar on how we do it. That means owning architecture decisions, driving them from proposal to production, and mentoring other engineers along the way.

Our platform spans ingestion from dozens of heterogeneous sources, orchestration, a cloud data warehouse, transformation layers, and the infrastructure underneath it all.

You won't just work on one slice: we expect seniors to be comfortable across the stack - from a dbt model that analysts depend on, to the Kubernetes workload that runs it, to the Terraform that provisions it, to the orchestration of all the pipelines involved.

You'll go deeper in some areas than others, and we'll make sure your depth is put to good use.

This is a hands-on engineering role with real ownership: you'll ship, operate what you ship, and shape the roadmap of the platform itself.

What you'll be doing

Design, build, and operate scalable data ingestion and processing pipelines across many source systems

Lead architectural decisions on the platform and write the proposals that get them adopted

Improve the reliability, observability, and cost-efficiency of the platform: if it pages someone at 9am, you'll want to know why and make it not happen again

Develop our infrastructure in close cooperation with Platform engineers

Work alongside analytics engineers, analysts and all data consumers to make the data experience more humane - better contracts, better tooling, better self-service

Mentor other data engineers through code review, pairing, and design feedback

Drive automation and AI-assisted operations: we'd rather build the tool than solve the same problem twice

Interact daily with other teams (analytics engineers, analysts, developers, platform engineers, product managers) to turn ambiguous data problems into shipped solutions

What will help you thrive in this role

Several years of experience building and operating production data platforms - data warehousing, data lakes, orchestration, and ingestion are the bread and butter of your experience, including events streaming

Strong Python and SQL skills with solid software engineering practices (testing, CI/CD, code review - you treat data code as code)

Deep experience with an orchestrator (we use Airflow): not just writing DAGs, but running, scaling, and debugging the thing itself

Strong experience with cloud platforms (we use AWS) and cloud data warehouses

Working knowledge of Docker and Kubernetes - you can deploy, inspect, and debug your own workloads

You've seen enough incidents to design for failure: idempotency, backfills, data quality checks, and monitoring are reflexes, not afterthoughts

You communicate like a senior: you can explain a technical trade-off to an analyst, a PM, or a fellow engineer - and you write things down properly

You're proactive and pragmatic: you don't just solve the problem, you ask why it happened, whether it's worth preventing, and what the simplest robust fix is

An eye on the future: you're excited by AI tools automating operational work, and you want to help us build toward that

You could help us in two areas

Depending on where your depth sits you could help us in one of two directions — one leaning a bit more towards the platform side, one a bit more towards enablement :

More platform-leaning : Kubernetes operations, Infrastructure as Code (Terraform), Docker optimization, and CI/CD; building and running the runtime layer that data workloads live on

More enablement-leaning : enabling different product areas in using the data platform, including ingestion, modeling through dbt and serving data to different scopes

In both directions: experience with streaming and message-driven architectures. We work with RabbitMQ, so that's a strong plus, but Kafka or similar counts too

A bonus either way: big data tooling (Spark) or experience operationalizing ML models.

We don't expect one person to be deep in all of the above: tell us where your spike is. Whichever direction you come from, the job is data engineering across the stack.

Why join Docplanner’s Data Platform Team?

You’ll be part of a tight-knit, cross-functional team of data engineers, analytics engineers and ML Ops engineers

We treat the data platform as a product - you’ll help build and improve it continuously, and as a senior you'll help decide where it goes next