Senior Data Engineer – Databricks

Cushman & Wakefield

. Drive the shift from a code-writing team to an AI orchestration team .

Posted 10/27/2026full-timeLisbon • PortugalSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in data modeling, production troubleshooting, and building scalable data solutions using advanced SQL, Python, and Databricks. Proven ability to design and implement automated ingestion pipelines and improve data quality metrics.

Highest-signal resume keywords

Advanced SQLPython ProficiencyDatabricks ExpertiseData Modeling ExperienceProduction Troubleshooting

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Data ModelingProduction TroubleshootingRoot Cause AnalysisAdvanced SQLPythonPySparkData EngineeringGeospatial Data ProcessingDeclarative PipelinesRecursive CTEs

Soft Skills

Strong Written CommunicationCuriosity

Tools & Technologies

DatabricksAzure EcosystemUnity CatalogGit Workflows

Industry Keywords

Data QualityAgentic WorkflowsCI/CDData GovernanceMDMGeocodingClient MasteringProfiling

Tech Stack

Tools & technologies

AzurePySparkPythonSparkSQLUnity

About the role

Key responsibilities & impact

Drive the shift from a code-writing team to an AI orchestration team
Build agentic workflows for data engineering tasks and CI/CD
Design semantic models for downstream consumption
Implement an AI Gateway for governance
Steward and incrementally improve the AI-amplified Databricks framework
Design data models that bring global sources into a coherent shape
Build data solutions for custom MDM, geocoding, client mastering, and profiling
Design and implement stable, automated ingestion pipelines from diverse sources
Own production troubleshooting and root cause analysis
Diagnose and resolve pipeline failures, performance issues, and data quality problems using code, logs, and documentation
Report on data quality and deliver improvements that increase quality metrics
Make consequential architectural decisions across key EMEA and APAC transformation projects
Work directly with the team lead and analytical engineers

Requirements

What you’ll need

Around 6 or more years of relevant experience
A degree in a quantitatively rigorous field such as computer science, data science, econometrics, mathematics, or physics
Systems thinking and ability to build for scale
Production troubleshooting and root cause analysis skills
Data modeling experience, including data products, data contracts, and complex business rules
Advanced SQL, including window functions, query optimization, and MERGE/UPSERT operations
Python and PySpark proficiency
Experience working with JSON, CSV, and Parquet
Deep experience with Databricks, including Declarative Pipelines, DABS, Delta Lake, Spark optimization, and job orchestration
Familiarity with the Azure ecosystem
Working understanding of Unity Catalog
Driven and curious approach to unresolved technical problems
Strong written communication, including async updates and clear documentation
Experience with agentic data engineering, coding agents, geospatial data processing, recursive CTEs, infrastructure, Git workflows, code review, or real estate domain knowledge are nice to have

Benefits

Comp & perks

Autonomy and ownership of how to deliver the high-level roadmap
Dedicated learning time
Team support and knowledge-sharing to develop skills
Rare growth path in emerging agentic data engineering capabilities
Established architecture, standards, and best practices
Equal opportunity, inclusive, and barrier-free workplace
Accessible accommodations during the hiring process for candidates with disabilities