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Senior Data Engineer

Sigma Software

Senior Data Engineer

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.

Job Description
  • 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
Qualifications
  • 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
Additional Information

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
Vacancy posted 2 days ago
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