We
are
hiring
a
Databricks
Data
Engineer
to design,
build
, and
operate
scalable
data
pipelines
and
curated
data
products
on
Databricks
.
You
will
work
across
ingestion
,
transformation
,
governance
, and
delivery
layers
—
using
SQL,
Python
, and
PySpark -
while
applying
strong
data
warehousing
principles
(
Kimball
).
This
role
requires
hands
-on
experience
with
Databricks
platform
capabilities
,
including
Unity
Catalog
and
Lakeflow
Declarative
Pipelines
, and a
disciplined
approach
to
quality
using
validation
/
expectations
.
Key
Responsibilities
Build
and
maintain
production-grade
data
pipelines
in
Databricks
using
SQL,
Python
, and
PySpark
.
Implement
ELT/ETL
patterns
for
batch
and (
where
relevant
)
streaming
data
processing
.
Develop
and
maintain
Lakehouse
data
models
and
curated
datasets
aligned
with
DWH
best
practices
(
Kimball
/
Inmon
/
Data
Vault
).
Use
Databricks-native
capabilities
to
implement
robust
,
maintainable
pipelines
(
e.g
.,
Lakeflow
Declarative
Pipelines
).
Implement
data
quality
checks
(
e.g
.,
Expectations
) and monitoring to
ensure
reliability
and trust in
data
products
.
Configure
and
manage
governance
and
access
controls
using
Unity
Catalog
,
including
catalogs
/
schemas
,
permissions
, and
lineage-friendly
practices
.
Optimize
performance
and
cost
(
cluster
sizing
,
partitioning
,
file
sizes
,
caching
,
query
optimization
).
Collaborate
with
analytics
,
data
science
, and
engineering
stakeholders
to
translate
requirements
into
well-defined
data
contracts
and
deliverables
.
Create
and
maintain
technical
documentation
for
pipelines
,
models
, and
operational
runbooks
.
Support
operational
excellence: incident
response
,
root-cause
analysis
, and
continuous
improvement
of
data
platform
reliability
.
Required
Qualifications
Proven
,
hands
-on
Databricks
experience
in
production
environments
.
Strong
working
knowledge
of SQL,
Python
, and
PySpark
for
data
engineering
workloads
.
Practical
experience
with
Databricks-specific
technologies
such
as:
Lakeflow
Declarative
Pipelines
(DLT)
Expectations
/
data
quality
validation
patterns
Unity
Catalog
(
governance
,
access
control
,
catalog
/
schema
management)
Other
Databricks
platform
components
relevant
to
pipeline
development
and
operations
Solid
experience
with
data
warehousing
design and modeling
methodologies
(
Kimball
,
Inmon
, or
Data
Vault
).
Understanding
of
data
engineering
fundamentals
:
orchestration
patterns
,
incremental
processing
,
SCDs
,
metadata
management, and
observability
.
Nice
-to-
Have
Qualifications
Experience
with
Microsoft SQL Server and T-SQL.
Experience
working
in
Azure
(
e.g
., ADLS,
Azure
networking
/
security
concepts
, identity/
auth
).
Proficiency
with
Git-
based
workflows
(
branching
,
code
reviews
) and CI/CD
for
data
pipelines
.
Working
Style
and
Collaboration
Ownership
mindset
:
you
build
it
,
you
run
it
.
Pragmatic
engineering
:
focus
on
reliability
,
clarity
, and
maintainability
over “
clever
.”
Strong
communication
:
ability
to
align
stakeholders
on
definitions
,
assumptions
, and
trade-offs
.
We offer:
A Truly Global Workplace – collaborate with 40+ nationalities across 25+ countries, embracing diversity, inclusion, and cross-cultural innovation
Hybrid & Flexible Work – balance your life and career with remote-friendly policies and modern offices across Europe
A Culture of Growth – accelerate your development with access to LinkedIn Learning, structured mentorship, and internal leadership programmes (HiPo & People Leader tracks)
Workation Programme – work remotely from abroad for up to 2 months per year and experience new cultures while staying connected and productive
Financial Growth Opportunities – invest in your future with our share purchase matching programme, doubling your contributions and fostering long-term rewards
Extra Time to Recharge – enjoy 4 fully paid sick days per year to rest when needed
Stay Active – access to the MultiSport card, supporting your fitness, wellness, and relaxation goals
Healthy Office Culture – enjoy fresh snacks and refreshments daily in a modern workspace
Up Benefia – choose the perks that suit you best with our flexible benefits system, giving you a set budget to spend on categories like fashion, wellness, dining, education, entertainment, and more
We may use artificial intelligence (AI) tools to support specific parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses against predefined criteria. These tools assist our recruitment team but do not replace human judgment. All final hiring decisions are made by human recruiters.
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