Senior Data Engineer
At a glance
Senior Data Engineering role at peakdata. Wrocław · contract.
Pay not stated Data Engineer salary
dataroles summary, based on the employer's posting.
What you'll do
- Build pipeline components as data flows are rebuilt, then maintain them and retire older services
- Turn data packages specified by data science into production-ready integrations
- Work with data scientists to move experiments and models into production
- Monitor infrastructure, improve reliability, and contribute to backend services where data meets product logic
What you bring
- At least four years in data engineering or backend engineering
- You write production-quality Python and can handle complex SQL, schema design, and query performance
- You have shipped services in Docker, rather than only running containers locally
Who this fits
This hands-on role suits a senior engineer who takes responsibility for deployed systems and can work across data science and backend teams. It is a contractor position for someone working from Poland, with a sole proprietorship required.
From the employer
About PeakData
PeakData provides AI-powered market intelligence that helps pharmaceutical companies
optimize drug launch execution and resource allocation. Our platform delivers actionable
insights on healthcare professionals (HCPs) and healthcare organizations (HCOs), giving
commercial leaders data-driven tools for decision-making.
The Team
The engineering team in Poland is structured around three areas: Data Science (2 people),
Backend/Data Engineering (4 people), and Frontend (2 people). You'd be joining the
backend/data engineering team.
You'll work closely with the DS on handoffs from experimentation to production, with the
Product Manager on scope and priorities, and with the broader backend team on platform
services where pipeline logic intersects with the product.
Role Overview
We're looking for a Senior Data Engineer to own data pipeline work end-to-end — from
building and maintaining production pipelines to integrating new data sources and
contributing to backend services that power the platform.
You'll be working on: developing new pipeline components as we revamp and upgrade our
data flows, cleaning up and sunsetting legacy services, maintaining and improving
infrastructure, and eventually integrating open data sources. When DS work produces a
new model or data package, you're the person who makes it production-ready.
This is a hands-on engineering role. Not research, not analytics.
Technical Environment
• Python — core language for everything
• SQL — daily use
• Docker — containerized services throughout
• AWS — Lambda, ECS, S3, Step Functions, CDK (experience a plus, not required
from day one)
• Data Stores: PostgreSQL, DynamoDB, BigQuery
• IaC: Terraform / CDK (nice to have)
• Orchestration: Argo (or similar — willingness to learn matters more than prior
experience)
What You'll Own
• Build new pipeline components as we upgrade and refactor data flows
• Maintain and improve existing data pipelines — including sunset work on legacy
services
• Integrate new data package sources after DS teams define the spec — you make it
production-grade
• Collaborate with data scientists on handoffs from experimentation to production
• Keep the infrastructure running: monitoring, alerting, reliability
• Contribute to backend services where data and platform logic intersects with the
product
What We're Looking For
Must-have:
• 4+ years in data engineering or backend engineering
• Strong Python — production-grade, not just scripts or notebooks
• SQL — comfortable with complex queries, schema design, performance
considerations
• Docker — you've shipped containerized services, not just run them locally
Nice to have:
• pandas / data wrangling experience
• AWS (any depth — Lambda, S3, ECS)
• Terraform or CDK
• Experience with orchestration tools (Argo, Airflow, Prefect, or similar)
• Prior work in regulated or data-sensitive environments (life sciences, healthcare,
finance)
What matters more than stack coverage:
• You take ownership of what you ship and monitor it
• You're used to working from a data spec that's 80% complete — you can fill the
gaps yourself and flag the ones you can't
• You can work across the DS ↔ backend boundary without needing a translator
What We're Not Looking For
• Full-stack generalists who drift toward frontend
• People who wait for a ticket to tell them something is broken
What we offer
Workthat matters – build solutions that support faster and more effective healthcare outcomes.
Hands-onAI work – practical experience with LLMs and modern AI applications used in real business scenarios.
FlexibleB2B compensation – €30–40/h depending on seniority (sole proprietorship only). Net invoicing, VAT settled on the Swiss side. Payments in EUR.
Remote-first setup– work from anywhere in Poland. Love good coffee and teamwork? You’re always welcome at our Wrocław office.
Long-termprojects with global pharma partners – stability, clear goals and meaningful work.
Growthopportunities – develop your skills, explore new tools and deepen your expertise in healthcare and data.
Join us and make your data skills matter.
Build your career in a stable international team shaping the future of healthcare.
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