Databricks Data Engineer

Multitude; Schweiz; Vor Ort; CHF 53.000 - 63.000; Vollzeit

Benefits dieser Stelle

Global workplace

Hybrid & Flexible Work

Growth & Learning

Share purchase matching

Workation program

Zusammenfassung

Multitude is 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, applying data warehousing principles (Kimball). The role requires hands-on experience with Unity Catalog, Lakeflow Declarative Pipelines, and strong data quality practices.

Qualifikationen

• Databricks production experience.
• SQL, Python, PySpark for data engineering workloads.
• Lakeflow DLt and data quality patterns.
• Unity Catalog governance and access control.
• Data warehousing design/methods: Kimball/Inmon/Data Vault.
• Orchestration patterns, incremental processing, SCDs, metadata observability.

Aufgaben

• Build and maintain production-grade Databricks pipelines using SQL, Python, and PySpark.
• Implement ELT/ETL patterns for batch and streaming data.
• Develop Lakehouse models and curated datasets aligned with Kimball/Inmon/Data Vault.
• Use Databricks capabilities (Lakeflow, Unity Catalog) for robust pipelines.
• Implement data quality checks and monitoring for reliability.
• Configure governance and access controls with Unity Catalog.
• Optimize performance and cost via clustering, partitioning, caching, and query tuning.
• Collaborate with analytics, data science, and engineering to define data contracts.
• Create and maintain technical docs and runbooks.
• Support operational excellence: incident response and root-cause analysis.

Kenntnisse

Databricks

SQL

Python

PySpark

Unity Catalog

Lakeflow DLt

Data quality

Data warehousing

Orchestration

SCDs

Metadata mgmt

Observability

Tools

Lakeflow Declarative Pipelines (DLT)

Jobbeschreibung

WearehiringaDatabricksDataEngineerto design,build, andoperatescalabledatapipelinesandcurateddataproductsonDatabricks.

Youwillworkacrossingestion,transformation,governance, anddeliverylayers—usingSQL,Python, andPySpark - whileapplyingstrongdatawarehousingprinciples(Kimball).

Thisrolerequireshands-onexperiencewithDatabricksplatformcapabilities,includingUnityCatalogandLakeflowDeclarativePipelines, and adisciplinedapproachtoqualityusingvalidation/expectations.

KeyResponsibilities

• Buildandmaintainproduction-gradedatapipelinesinDatabricksusingSQL,Python, andPySpark.

• ImplementELT/ETLpatternsforbatchand (whererelevant)streamingdataprocessing.

• DevelopandmaintainLakehousedatamodelsandcurateddatasetsalignedwithDWHbestpractices(Kimball/Inmon/DataVault).

• UseDatabricks-nativecapabilitiestoimplementrobust,maintainablepipelines(e.g.,LakeflowDeclarativePipelines).

• Implementdataqualitychecks(e.g.,Expectations) and monitoring toensurereliabilityand trust indataproducts.

• ConfigureandmanagegovernanceandaccesscontrolsusingUnityCatalog,includingcatalogs/schemas,permissions, andlineage-friendlypractices.

• Optimizeperformanceandcost(clustersizing,partitioning,filesizes,caching,queryoptimization).

• Collaboratewithanalytics,datascience, andengineeringstakeholderstotranslaterequirementsintowell-defineddatacontractsanddeliverables.

• Createandmaintaintechnicaldocumentationforpipelines,models, andoperationalrunbooks.

• Supportoperationalexcellence: incidentresponse,root-causeanalysis, andcontinuousimprovementofdataplatformreliability.

RequiredQualifications

• Proven,hands-onDatabricksexperienceinproductionenvironments.

• Strongworkingknowledgeof SQL,Python, andPySparkfordataengineeringworkloads.

• PracticalexperiencewithDatabricks-specifictechnologiessuchas:

• LakeflowDeclarativePipelines(DLT)

• Expectations/dataqualityvalidationpatterns

• UnityCatalog(governance,accesscontrol,catalog/schemamanagement)

• OtherDatabricksplatformcomponentsrelevanttopipelinedevelopmentandoperations

• Solidexperiencewithdatawarehousingdesign and modelingmethodologies(Kimball,Inmon, orDataVault).

• Understandingofdataengineeringfundamentals:orchestrationpatterns,incrementalprocessing,SCDs,metadatamanagement, andobservability.

Nice-to-HaveQualifications

• ExperiencewithMicrosoft SQL Server and T-SQL.

• ExperienceworkinginAzure(e.g., ADLS,Azurenetworking/securityconcepts, identity/auth).

• ProficiencywithGit-basedworkflows(branching,codereviews) and CI/CDfordatapipelines.

WorkingStyleandCollaboration

• Ownershipmindset:youbuildit,yourunit.

• Pragmaticengineering:focusonreliability,clarity, andmaintainabilityover “clever.”

• Strongcommunication:abilitytoalignstakeholdersondefinitions,assumptions, andtrade-offs.

The starting salary for this position is €5,500 per month (B2B type of cooperation).

We offer:

• A Truly Global Workplace – work with professionals from 40+ nationalities, bringing diverse expertise, perspectives, and a collaborative international culture.

• Hybrid & Flexible Work – we support work-life balance with remote work options and modern office spaces across Europe.

• A Culture of Growth – we invest in your future, offering LinkedIn Learning, mentorship, and professional development programmes, including HiPo and leadership development initiatives to support career advancement.

• Financial Growth Opportunities – benefit from our share purchase matching programme, allowing you to invest in your future with matched contributions and long‑term financial rewards.

• Workation Programme – work remotely from different countries for up to 2 months per year, experiencing new cultures while staying connected and productive.

We may use artificial intelligence (AI) tools to support specific parts of the hiring process, such as reviewing applications, analyzingresumes, 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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