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Wallet icon Coin icon Rate 6 000 € - 7 000 € / month info
Timer icon Form of cooperation Full-time / 80% Remote
Briefcase icon Sector Insurance
Location icon Location Bratislava

info The reward is calculated upon delivery of 20 MD per month (1MD=8h)

Project duration 12 months with the possibility of extension
Period of cooperation 01.08.2026 - 31.07.2027
Start date 01.08.2026 ASAP or by agreement
Project duration 12 months with the possibility of extension
Period of cooperation 01.08.2026 - 31.07.2027
Start date 01.08.2026 ASAP or by agreement
Technology
  • ETL
  • SQL
  • GIT
  • Python
  • Lakehouse
  • PySpark
  • Databricks
Languages
  • English flag English - active, B2/C1/C2
  • Slovak or Czech flag Slovak or Czech - native

Project description

  • cooperation within the newly formed team of the Risk Accumulation Management Platform (RAMP) and will be responsible for designing the data architecture, building ETL pipelines, and migrating data to a modern Databricks Lakehouse environment
    • the goal is to centralize, analyze, and provide real-time access to insurance risk data
  • the project is part of a strategic initiative focused on modernizing risk exposure management across the company's insurance portfolio
  • responsibility for building the data foundations of the entire platform:
    • data model design
    • historical data migration
    • ETL process development
    • data quality implementation
    • underwriting pipeline integration
    • Databricks Lakehouse architecture optimization
  • the project combines modern cloud data technologies with business-critical insurance and risk management processes
  • tasks and responsibilities:
    • design and implementation of the data model for risk accumulation reporting
    • data modeling for:
      • catastrophe exposure
      • accumulation reporting
      • underwriting pipeline
      • historical exposures
    • design and implementation of ETL/ELT processes
    • data migration from legacy systems to the Databricks platform
    • development and optimization of PySpark transformations
    • design and management of Delta Lake layers
    • building data pipelines for:
      • ingestion
      • transformation
      • aggregation
      • snapshot management
    • implementation of data quality and validation mechanisms
    • monitoring of data flows
    • cooperation with:
      • underwriters
      • actuaries
      • catastrophe modelers
      • business stakeholders
    • support for API Developers and other team members
    • participation in the design of the platform's data architecture
  • technologies used
    • Must-have stack
      • Databricks
      • Delta Lake
      • PySpark
      • Python
      • SQL
      • ETL / ELT
      • Lakehouse Architecture
      • Git
    • Project stack
      • Databricks Workflows
      • Job Orchestration
      • Data Quality Frameworks
      • CI/CD
      • DevOps
      • Risk Data Modelling
      • Snapshot Management
      • Data Governance
    • Nice-to-have
      • Azure Data Factory
      • Azure Storage
      • Azure SQL
      • Feature Serving
      • Model Serving
      • Data Cataloguing
      • Insurance Data Models
      • Catastrophe Exposure Models
      • Reinsurance Systems
         
  • cooperation possible in a HYBRID REMOTE + ON-SITE mode [1 day per week, Bratislava], or by further agreement with the client
  • the final remuneration depends on the candidate's experience and the selection process

Project requirements

  • minimum 4+ years of experience as a Data Engineer
  • excellent knowledge of:
    • SQL
    • data modeling
  • advanced experience with:
    • Python
    • PySpark
    • Pandas
    • NumPy
  • experience with:
    • Databricks
    • Delta Lake
    • Lakehouse architecture
  • experience with design of:
    • ETL/ELT pipeline
    • data transformations
    • data quality
  • knowledge of:
    • Git
    • CI/CD
    • DevOps principles
  • ability to design scalable data solutions
     
  • active knowledge of English language at a communicative level (min. B2-C1)
     
  • a big advantage:
    • Azure Data Services
    • Azure Data Factory
    • Azure Storage
    • Azure SQL
    • Feature Serving
    • Model Serving
    • experience from:
      • insurance industry
      • financial sector
      • risk management
    • experience with:
      • Data Governance
      • Data Cataloguing
      • Master Data Management
         
  • strong analytical and organizational skills
  • ability to effectively solve problems
  • independence and willingness to learn
  • strong interpersonal and communication skills (written and verbal)
  • team player
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