JOB DETAILS

Databricks Data Engineer

CompanyMultitude
LocationBratislava
Work ModeOn Site
PostedJune 1, 2026
About The Company
Multitude Bank p.l.c., a subsidiary of Multitude SE, is licenced by the Malta Financial Services Authority to provide a range of banking services to its clients. Its EU banking licence enables it to provide its services from Malta to other jurisdictions within the EEA, including the acceptance of deposits, which are covered by the Maltese Depositor Compensation Scheme. Multitude Bank is the backbone of the Multitude growth platform, offering various banking services to customers via different brands. The Bank offers its customers secure and professional deposit and personal loan solutions at speed, with the simplicity and openness of our uncomplicated and efficient online service. In many cases, loans can be approved within a matter of minutes. Our success lies in our simple processes, quick service and strict security. The experience is further enriched by the expertise of our employees whose dedication, know-how and service skills retain customers and gain referrals all over the world. Multitude Bank p.l.c. is a public limited company, registered under the laws of Malta with number C56251, with its registered address at ST Business Centre 120, The Strand, Gzira, GZR 1027, Malta. Multitude Bank p.l.c. is licensed as a credit institution by the Malta Financial Services Authority, Notabile Road, BKR 3000, Attard, Malta (http://www.mfsa.com.mt/). Details on how the Bank is regulated by the Malta Financial Services Authority are available upon request.
About the Role

 

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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Key Skills
DatabricksSQLPythonPySparkUnity CatalogLakeflow Declarative PipelinesKimball MethodologyData WarehousingETL/ELTData ModelingData Quality ValidationAzureGitCI/CDMicrosoft SQL ServerT-SQL
Categories
Data & AnalyticsTechnologySoftwareEngineeringFinance & Accounting
Benefits
Global WorkplaceHybrid & Flexible WorkLinkedIn LearningStructured MentorshipInternal Leadership ProgrammesWorkation ProgrammeShare Purchase Matching ProgrammePaid Sick DaysMultiSport CardFresh Snacks and RefreshmentsFlexible Benefits System
Job Information
📋Core Responsibilities
Design, build, and operate scalable data pipelines and curated data products using Databricks, SQL, Python, and PySpark. Manage data governance via Unity Catalog and ensure data reliability through quality checks and performance optimization.
📋Job Type
full time
📊Experience Level
5-10
💼Company Size
55
📊Visa Sponsorship
No
💼Language
English
🏢Working Hours
40 hours
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