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[GFA] Azure Senior Data Engineer

Kraków, Lesser Poland Voivodeship, Poland

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Employment
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Apply at Software Mind

What you’ll bring

All qualifications

Core experience

  • Data modeling mastery: extensive experience in data model definition including fact tables, dimension tables, measures, grain analysis, SCD Type 2, surrogate keys, late-arriving records handling, overlap joins, and incremental loads with idempotency
  • Understanding of stream processing challenges and Spark Structured Streaming
  • SQL proficiency: strong SQL skills for complex data transformations
  • Experience with Infrastructure as Code (Terraform, Bicep)
  • Experience with containerized applications (Azure Container Apps, Kubernetes)
  • Knowledge of Azure cloud native solutions (Azure Data Factory, Azure Function App, Azure Container Instances)
Qualification wording
Data modeling mastery: extensive experience in data model definition including fact tables, dimension tables, measures, grain analysis, SCD Type 2, surrogate keys, late-arriving records handling, overlap joins, and incremental loads with idempotency
Understanding of stream processing challenges and Spark Structured Streaming
SQL proficiency: strong SQL skills for complex data transformations
Experience with Infrastructure as Code (Terraform, Bicep)
Experience with containerized applications (Azure Container Apps, Kubernetes)
Knowledge of Azure cloud native solutions (Azure Data Factory, Azure Function App, Azure Container Instances)

Tools in this posting

  • Python
  • SQL
  • Azure
  • Databricks
  • Spark
  • Terraform
  • PySpark
  • Kubernetes
Source — Tool mentions in context
- Data modeling mastery: extensive experience in data model definition including fact tables, dimension tables, measures, grain analysis, SCD Type 2, surrogate keys, late-arriving records handling, overlap joins, and incremental loads with idempotency - Programming: advanced Python and PySpark skills for ETL/ELT development - Databricks optimization: deep knowledge of optimize, zOrder, Liquid clustering, ACID transactions and performance tuning
- Azure data platform: experience working with Azure-based datasets and data pipelines - SQL proficiency: strong SQL skills for complex data transformations - Large-scale data processing: experienced in handling large and complex datasets efficiently
Our customer provides innovative solutions and insights that enable our clients to manage risk and hire the best talent. Their advanced global technology platform supports fully scalable, configurable screening programs that meet the unique needs of over 33,000 clients worldwide. Headquartered in Atlanta, GA, they have an internationally distributed workforce spanning 19 countries with about 5,500 employees. Our partner perform over 93 million screens annually in over 200 countries and territories. We are seeking a Senior Data Engineer with proven expertise in Databricks PySpark development, comprehensive data modeling experience (including fact/dimension tables, SCD Type 2 and incremental loads) and event-based architecture skills to join our Data Engineering Team and drive the evolution of our Azure-based Data Analytics Platform. Position – how you’ll contribute
- Event-based architecture: proven experience in designing and implementing event-driven data solutions - Azure data platform: experience working with Azure-based datasets and data pipelines - SQL proficiency: strong SQL skills for complex data transformations
- Experience with Infrastructure as Code (Terraform, Bicep) - Experience with containerized applications (Azure Container Apps, Kubernetes) - Knowledge of Azure cloud native solutions (Azure Data Factory, Azure Function App, Azure Container Instances)
- Experience with containerized applications (Azure Container Apps, Kubernetes) - Knowledge of Azure cloud native solutions (Azure Data Factory, Azure Function App, Azure Container Instances) Additional Information
Position – how you’ll contribute - Develop reusable, metadata-driven data pipelines using Databricks Lakehouse architecture and PySpark - Design and implement comprehensive data models
Expectations – the experience you need - Databricks expertise: proficient in Databricks Lakehouse architecture and PySpark development - Data modeling mastery: extensive experience in data model definition including fact tables, dimension tables, measures, grain analysis, SCD Type 2, surrogate keys, late-arriving records handling, overlap joins, and incremental loads with idempotency
- Programming: advanced Python and PySpark skills for ETL/ELT development - Databricks optimization: deep knowledge of optimize, zOrder, Liquid clustering, ACID transactions and performance tuning - Event-based architecture: proven experience in designing and implementing event-driven data solutions
Additional skills – the edge you have - Understanding of stream processing challenges and Spark Structured Streaming - Experience with Infrastructure as Code (Terraform, Bicep)
- Understanding of stream processing challenges and Spark Structured Streaming - Experience with Infrastructure as Code (Terraform, Bicep) - Experience with containerized applications (Azure Container Apps, Kubernetes)

Job description

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Job Description

Project – the aim you’ll have

Our customer provides innovative solutions and insights that enable our clients to manage risk and hire the best talent. Their advanced global technology platform supports fully scalable, configurable screening programs that meet the unique needs of over 33,000 clients worldwide. Headquartered in Atlanta, GA, they have an internationally distributed workforce spanning 19 countries with about 5,500 employees. Our partner perform over 93 million screens annually in over 200 countries and territories.

We are seeking a Senior Data Engineer with proven expertise in Databricks PySpark development, comprehensive data modeling experience (including fact/dimension tables, SCD Type 2 and incremental loads) and event-based architecture skills to join our Data Engineering Team and drive the evolution of our Azure-based Data Analytics Platform.

Position – how you’ll contribute

  • Develop reusable, metadata-driven data pipelines using Databricks Lakehouse architecture and PySpark
  • Design and implement comprehensive data models
  • Build robust ETL/ELT solutions with advanced features: Merge operations, SCD Type 2 implementations, etc.
  • Implement incremental data loads with idempotency patterns and overlap joins optimization
  • Automate and optimize data platform processes with focus on performance and reliability
  • Build integrations with data sources and consumers using event-driven patterns
  • Cooperate with infrastructure engineering team to set up cloud resources
  • Initiate and implement improvements to data platform architecture

Qualifications

Expectations – the experience you need

  • Databricks expertise: proficient in Databricks Lakehouse architecture and PySpark development
  • Data modeling mastery: extensive experience in data model definition including fact tables, dimension tables, measures, grain analysis, SCD Type 2, surrogate keys, late-arriving records handling, overlap joins, and incremental loads with idempotency
  • Programming: advanced Python and PySpark skills for ETL/ELT development
  • Databricks optimization: deep knowledge of optimize, zOrder, Liquid clustering, ACID transactions and performance tuning
  • Event-based architecture: proven experience in designing and implementing event-driven data solutions
  • Azure data platform: experience working with Azure-based datasets and data pipelines
  • SQL proficiency: strong SQL skills for complex data transformations
  • Large-scale data processing: experienced in handling large and complex datasets efficiently
  • CI/CD: experience in developing automated deployment pipelines
  • Networking fundamentals: understanding of basic networking concepts
  • Agile methodology: familiar with Scrum and agile development practices

Additional skills – the edge you have

  • Understanding of stream processing challenges and Spark Structured Streaming
  • Experience with Infrastructure as Code (Terraform, Bicep)
  • Experience with containerized applications (Azure Container Apps, Kubernetes)
  • Knowledge of Azure cloud native solutions (Azure Data Factory, Azure Function App, Azure Container Instances)

Additional Information

Our offer – professional development, personal growth:

  • Flexible employment and remote work  
  • International projects with leading global clients 
  • International business trips  
  • Non-corporate atmosphere 
  • Language classes 
  • Internal & external training 
  • Private healthcare and insurance  
  • Multisport card 
  • Well-being initiatives 

Position at: Software Mind Poland

This role requires candidates to be based in Poland.

Company Description

Software Mind develops solutions that make an impact for companies around the globe. Tech giants & unicorns, transformative projects, emerging technologies and limitless opportunities – these are a few words that describe an average day for us. Building cross-functional engineering teams that take ownership and crave more means we’re always on the lookout for talented people who bring passion and creativity to every project. Our culture embraces openness, acts with respect, shows grit & guts and combines employment with enjoyment.

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Source & posting history

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Pay

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Location & working pattern

Kraków, Lesser Poland Voivodeship, Poland

Our offer – professional development, personal growth: - Flexible employment and remote work - International projects with leading global clients
Work authorization

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Status in our records
Active
First seen by us
Jul 9, 2026
Recorded sightings
170
Last seen by us
Oct 8, 2026

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