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Day 152
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Senior Data Engineer
- Pay
€30–40/h — pay source
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.
Read the full posting- Work setting
- Not stated
- Employment
Contract — employment source
Employment type in the employer’s posting: Contractor
From the employer’s posting
What you’ll work on
Full postingWe'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
Build new pipeline components as data flows are upgraded and refactored
Maintain and improve existing pipelines, including sunsetting legacy services
Integrate new data sources once data science teams define the spec
Hand off data science models and packages to production
Keep infrastructure reliable through monitoring and alerting
From the employer’s posting
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
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
What you’ll bring
All qualificationsCore experience
- 4+ years in data or backend engineering
- Strong production-grade Python
- Complex SQL, schema design and performance work
- Docker containerized services shipped to production
Qualification wording
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
Benefits in the posting
Full benefits wording- Workthat matters – build solutions that support faster and more effective healthcare outcomes.
- FlexibleB2B compensation – €30–40/h depending on seniority (sole proprietorship only). Net invoicing, VAT settled on the Swiss side. Payments in EUR.
- Growthopportunities – develop your skills, explore new tools and deepen your expertise in healthcare and data.
- Build your career in a stable international team shaping the future of healthcare.
From the employer’s posting.
About PeakData
PeakData provides AI-powered market intelligence that helps pharmaceutical companies optimize drug launch execution and resource allocation.
In the employer’s words · Read in context
Posting record
Report an errorOpen 5 monthsWe first saw this posting 152 days ago and it is still up. Roles open this long are often slow to fill or kept open to collect applications.
- Status in our records
- Live
- First seen by us
- Jun 4, 2026152 days ago
- Recorded sightings
- 64
- Last seen by us
- Nov 3, 2026
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
How this job compares
PeakData is hiring
1 open job
Hiring recordSee how this role fits your experience
Add your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.
- Python
- SQL
- AWS
- BigQuery
- Docker
- DynamoDB
- PostgreSQL
- Prefect
- S3
- Terraform
- Airflow
Where the posting names them
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
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:
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:
Your next step
Complete your application on peakdata.bamboohr.com. The employer’s form will show what is required.
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Already applied? Track this application
About the role
We file this job under Data Engineer, by the work the posting describes.
Data engineers build and run the pipelines that copy data out of apps and outside services into a warehouse or lake, and fix them when a source changes or a load fails.
Expect SQL, Python, a cloud platform, a scheduler such as Airflow, and often tools for large data such as Spark or Kafka.
An analytics engineer works one step later, turning the raw data a data engineer lands into clean tables people can query.
US government figures for database architects
- Median yearly pay, May 2025
- $139,500
- Expected change, 2025 to 2035
- 9.4% more jobsagainst 3.5% for all jobs
The government has no code for data engineers, so these figures are for the closest group, database architects, which includes data integration and data warehousing specialists.
Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-1243.
Job description
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.
Source details
Source notes
Source excerptsSelected passages from the saved posting. Check the full description for conditions and exceptions.
- Pay
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.
- Location & working pattern
Location not supplied.
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.
- Work authorization
No clear work-authorization passage found. Eligibility is unconfirmed.