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Senior Data Engineer

Warsaw, Masovian Voivodeship, Poland

Pay
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Work setup
Unconfirmed
Employment
Unconfirmed
Apply at Sigma Software

What you’ll bring

All qualifications

Core experience

  • 5+ years of professional experience in Data Engineering
  • Familiarity with RAG pipeline design and LLM integration patterns
  • Strong Python and SQL development skills
  • Knowledge of data governance frameworks and tools such as Unity Catalog or Apache Atlas
  • Hands-on experience with Apache Spark and PySpark including query optimization and performance tuning
  • Experience with dbt for data transformation and modelling
Qualification wording
5+ years of professional experience in Data Engineering
Familiarity with RAG pipeline design and LLM integration patterns
Strong Python and SQL development skills
Knowledge of data governance frameworks and tools such as Unity Catalog or Apache Atlas
Hands-on experience with Apache Spark and PySpark including query optimization and performance tuning
Experience with dbt for data transformation and modelling

Tools in this posting

  • Python
  • SQL
  • AWS
  • Azure
  • Databricks
  • dbt
  • Kafka
  • MLflow
  • Spark
  • Airflow
  • PySpark
  • Google Cloud (GCP)
  • Snowflake
  • Terraform
Source — Tool mentions in context
- 5+ years of professional experience in Data Engineering - Strong Python and SQL development skills - Hands-on experience with Apache Spark and PySpark including query optimization and performance tuning
- Experience working with Databricks or Snowflake - Practical experience with at least one major cloud provider such as Azure, AWS, or GCP - Experience with stream processing technologies including Kafka or Spark Structured Streaming
- Strong understanding of ETL/ELT patterns, data modelling, and data warehousing concepts - Experience with orchestration tools such as Apache Airflow or Azure Data Factory - Knowledge of Infrastructure as Code tools including Terraform
- Hands-on experience with Apache Spark and PySpark including query optimization and performance tuning - Experience working with Databricks or Snowflake - Practical experience with at least one major cloud provider such as Azure, AWS, or GCP
- Knowledge of data governance frameworks and tools such as Unity Catalog or Apache Atlas - Experience with dbt for data transformation and modelling - Familiarity with MLflow, Feature Stores, or ML platform integrations
- Practical experience with at least one major cloud provider such as Azure, AWS, or GCP - Experience with stream processing technologies including Kafka or Spark Structured Streaming - Strong understanding of ETL/ELT patterns, data modelling, and data warehousing concepts
- Experience with dbt for data transformation and modelling - Familiarity with MLflow, Feature Stores, or ML platform integrations Additional Information
- Define and enforce data platform standards including Data Lake and Lakehouse principles, medallion architecture, and data contracts - Refactor, optimize, and modernize Spark and PySpark scripts for performance and maintainability - Introduce best practices for code quality, testing, and CI/CD across data pipelines
- Strong Python and SQL development skills - Hands-on experience with Apache Spark and PySpark including query optimization and performance tuning - Experience working with Databricks or Snowflake
- Experience with orchestration tools such as Apache Airflow or Azure Data Factory - Knowledge of Infrastructure as Code tools including Terraform - Understanding of production-grade systems including observability, scalability, reliability, and performance

Job description

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Job Description

  • Design and build scalable cloud-native data platforms from greenfield to production
  • Design and implement near-real-time ingestion pipelines using event-driven patterns
  • Define and enforce data platform standards including Data Lake and Lakehouse principles, medallion architecture, and data contracts
  • Refactor, optimize, and modernize Spark and PySpark scripts for performance and maintainability
  • Introduce best practices for code quality, testing, and CI/CD across data pipelines
  • Drive adoption of AI tooling and agentic workflows within the Data Engineering team
  • Ensure data quality, observability, scalability, and reliability across all platforms and pipelines
  • Design and deliver self-service tooling and microservices that simplify platform usage
  • Collaborate with cross-functional stakeholders including Product, Machine Learning, and Data Science teams
  • Contribute to architecture decisions and technical R&D initiatives

Qualifications

  • 5+ years of professional experience in Data Engineering
  • Strong Python and SQL development skills
  • Hands-on experience with Apache Spark and PySpark including query optimization and performance tuning
  • Experience working with Databricks or Snowflake
  • Practical experience with at least one major cloud provider such as Azure, AWS, or GCP
  • Experience with stream processing technologies including Kafka or Spark Structured Streaming
  • Strong understanding of ETL/ELT patterns, data modelling, and data warehousing concepts
  • Experience with orchestration tools such as Apache Airflow or Azure Data Factory
  • Knowledge of Infrastructure as Code tools including Terraform
  • Understanding of production-grade systems including observability, scalability, reliability, and performance
  • Ability to independently lead technical initiatives from concept to delivery
  • Strong communication and collaboration skills
  • Upper-Intermediate or higher English level

WILL BE A PLUS

  • Familiarity with RAG pipeline design and LLM integration patterns
  • Knowledge of data governance frameworks and tools such as Unity Catalog or Apache Atlas
  • Experience with dbt for data transformation and modelling
  • Familiarity with MLflow, Feature Stores, or ML platform integrations

Additional Information

PERSONAL PROFILE

  • Proactive and self-driven mindset
  • Strong analytical and architectural thinking
  • Ability to work independently and take ownership of technical decisions
  • Passion for innovation and modern engineering practices
  • Knowledge-sharing and team-oriented approach
  • Strong problem-solving skills

Company Description

We are looking for a Senior Data Engineer to join our Data Engineering Team and take ownership of high-impact, greenfield data initiatives. You will work on building modern cloud-native data platforms, migrating on-premises legacy systems to the cloud, and laying the architectural foundation for AI-ready data infrastructure. 

In this role, you will collaborate closely with Machine Learning, Data Science, and Product teams, serving as a key technical contributor and thought leader. You will also drive R&D efforts around agentic AI architectures, event-driven systems, and LLM-ready data pipelines – turning architectural concepts into production-grade solutions.

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Source & posting history

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Pay

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Location & working pattern

Warsaw, Masovian Voivodeship, Poland

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Status in our records
Active
First seen by us
Oct 9, 2026
Recorded sightings
4
Last seen by us
Oct 10, 2026

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