Senior Data Engineer

About Qualifyze,
Founded in **, Qualifyze is a leading company in supply chain compliance management in the Life Sciences industry, trusted by over 1,500 pharmaceutical and healthcare companies globally.
Our digital suite of solutions connects manufacturers, suppliers, and a global network of more than 250 auditors and quality experts.
With a track record of over 4,500 audits across 85+ countries and the largest and most accurate supplier network and data analytics tools, Qualifyze stands as the all-in-one partner for quality compliance and supply chain risk mitigation in the Life Sciences sector.
Role Overview:
We are looking for a
Senior Data Engineer
to join our growing
Product & Tech team
.
In this role, you will help build and evolve our
data platform
,
owning key pipelines
and
data products
from end to end and contributing to the
engineering decisions
that shape them.
Your main goal will be to
design, build, and maintain reliable data pipelines
across our
operational databases
and
analytical platform
, applying
quality software engineering practices
to everything you ship.
You will collaborate closely with the
product team
and
backend engineers
, and work directly with
business stakeholders
who depend on
accurate, timely data
to drive
product decisions
.
This role is well suited for someone with
strong skills in Python and SQL
,
solid software engineering fundamentals
, hands?on experience building
production data pipelines
in a
product or platform team
, and a passion for managing work across the
full data cycle
, from
operational to analytical systems
.
Main responsibilities:
Design, build, and maintain
scalable, reliable, and well-tested
data pipelines
and
data products
.
Manage features and pipelines end-to-end
: from
schema design
in
operational databases
through
ingestion
,
transformation
, and
delivery of analytical datasets
.
Contribute to the
architecture
of our
data platform
and help evaluate
technical trade-offs
with the team.
Apply and help improve standards for
data modeling
,
data quality
,
testing
, and
code review
.
Work with
Product
,
Engineering
, and
business stakeholders
to turn requirements into
well-scoped data solutions
.
Monitor, troubleshoot, and resolve
pipeline incidents
, and improve
observability
and
reliability
over time.
Share knowledge
with the team and
mentor fellow engineers
through
pairing
and
code reviews
.
Main requirements:
Proficiency in
Python
for data engineering: building
robust ETL/ELT pipelines
and
reusable modules
, with
strong testing
(e.g., pytest) and
good observability
.
Strong SQL skills with PostgreSQL
: complex query design, performance tuning, indexing, and reading execution plans for both OLTP and OLAP workloads.
Hands?on experience with dbt
: building, testing, and documenting models, ideally in a layered (e.g., medallion) project structure.
Experience with
Dagster
(or similar orchestrators such as Airflow): building assets/jobs, scheduling, monitoring, and handling failures in production workflows.
Working knowledge of Docker and Kubernetes
: packaging and running data services and batch jobs in production.
Solid grasp of data modeling
: dimensional modeling and an understanding of the trade?offs between operational and analytical schemas.
Nice to have:
Experience with
AWS
(S3, EKS, Secrets Manager).
Experience with
database schema migration tools
(such as Liquibase) or
data contracts
.
Salary
At Qualifyze, our salary ranges are transparent internally, and we aim to follow a similar approach externally.
For this role, we're happy to share a reference point within the band: the expected salary range is around
**€ – **** €
, centered around the median.
Final compensation will depend on experience and performance during the process, with some flexibility within the range.
What do we offer?
Competitive, annually reviewed compensation package
Country vacation package that increases with your tenure
Country specific benefits offering incl.
private health care, fitness and meal allowances
Annual personal development budget to increase your impact
Hybrid working mode, plus up to 3 months of the year work from anywhere.
All the best kit and tools to work effectively
Annual in person all company event and celebration in Europe
Working with an exceptional team, doing some of the best work of your career
Use of AI in Our Re