Sigma Software
- Design and build scalable, cloud-native data platforms from greenfield to production
- Implement near-real-time ingestion pipelines using event-driven patterns
- Define and enforce platform standards, including Data Lake / Lakehouse principles, medallion architecture, and data contracts
- Refactor and optimise existing 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, and reliability across all pipelines and platforms
- Develop self-service tooling and microservices to simplify platform usage for other teams
- 5+ years of professional experience in Data Engineering
- Strong Python and SQL development skills for pipeline development and optimisation
- Proficiency in Apache Spark / PySpark, including query optimisation and performance tuning
- Hands-on experience with Databricks (preferred) or Snowflake
- Experience with at least one major cloud provider: Azure (preferred), AWS, or GCP
- Experience with stream processing technologies (Kafka, Spark Structured Streaming)
- Solid understanding of ETL/ELT patterns, data modelling (dimensional, Data Vault), and data warehousing
- Experience with orchestration tools (Apache Airflow, Azure Data Factory, or equivalent)
- Knowledge of Infrastructure as Code (Terraform or equivalent)
- Understanding of production-grade system requirements: reliability, scalability, observability, and performance
- Upper-Intermediate English level
WILL BE A PLUS
- Familiarity with RAG pipeline design and LLM integration patterns
- Knowledge of data governance frameworks and tools (Unity Catalog, Apache Atlas, or similar)
- Experience with dbt for data transformation and modelling
- Familiarity with MLflow, Feature Stores, or ML platform integration
PERSONAL PROFILE
- Self-driven and proactive in identifying improvements
- Comfortable working in a fast-paced, innovative environment
- Strong problem-solving mindset with attention to detail
- Open to experimenting with emerging technologies and approaches
Are you passionate about building cutting-edge, AI-ready data platforms from the ground up? We are looking for a Senior Data Engineer to join our Data Engineering Team and lead high-impact, greenfield 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.
Originally posted on Himalayas
To apply for this job please visit himalayas.app.
About this role & career path
Working in Poland
Poland, officially the Republic of Poland, is a country in Central Europe. It extends from the Baltic Sea in the north to the Sudetes and Carpathian Mountains in the south, and borders Lithuania and Russia to the northeast; Belarus and Ukraine to the east; Slovakia and the Czech Republic to the south; and Germany to the west. The territory has a varied landscape, diverse ecosystems, and a temperate climate. Poland is composed of sixteen voivodeships and is the fifth most populous member state of the European Union (EU), with over 38 million people, and the fifth largest EU country by land area
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