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Sigma Software Group
Sigma Software Group
1001 – 5000 Darbinieki
AutobūveKonsultācijasVeselības aprūpe
Sigma Software Group ir 2002. gadā dibināts starptautisks tehnoloģiju konsultāciju uzņēmums. Tā komandas nodrošina programmatūras izstrādi, grafisko dizainu, testēšanu un tehnisko atbalstu klientiem, kas darbojas tādās nozarēs kā autobūve, veselības aprūpe, telekomunikācijas, aviācija, banku darbība, spēļu industrija, nekustamais īpašums un reklāma. Uzņēmums pieņem darbā IT speciālistus darbam pie sarežģītiem inženierijas projektiem un atbalsta profesionālo izaugsmi, izmantojot mentoringu un nepārtrauktu mācīšanos. Attālinātā darba iespējas ir daļa no uzņēmuma darba modeļa, un projekti tiek īstenoti tādām organizācijām kā AstraZeneca, Scania un SAS.
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Vakances uzņēmumā

Senior Data Engineer

Build cloud-native data platforms and near-real-time pipelines, while modernizing Spark and PySpark workloads. Lead the adoption of AI tools and agentic workflows and contribute to technical research and development.

PLPolijaAttālinātiPilna slodzeVecākais speciālistsNepieciešamā Valoda: angļuDatu inženieris
AirflowApacheAWSAzureETLGoogle Cloud PlatformKafkaMākonisMikropakalpojumiPySparkPythonSparkSQLTerraform

Apraksts

  • Build scalable cloud-native data platforms from initial design through production.
  • Develop near-real-time ingestion pipelines using event-driven patterns.
  • Set and uphold platform standards for data lakes, lakehouses, medallion architecture, and data contracts.
  • Improve Spark and PySpark scripts for performance and maintainability.
  • Establish code quality, testing, and CI/CD practices across data pipelines.
  • Promote AI tools and agentic workflows within the Data Engineering team.
  • Maintain data quality, observability, scalability, and reliability across platforms and pipelines.
  • Create self-service tools and microservices that make the platform easier to use.
  • Work with Product, Machine Learning, and Data Science teams.
  • Contribute to architecture decisions and technical research and development.

Prasības

  • Bring at least five years of professional Data Engineering experience.
  • Demonstrate strong Python and SQL development skills.
  • Have hands-on Apache Spark and PySpark experience, including query optimization and performance tuning.
  • Have experience with Databricks or Snowflake.
  • Have practical experience with at least one major cloud provider: Azure, AWS, or GCP.
  • Have experience with stream processing tools such as Kafka or Spark Structured Streaming.
  • Understand ETL/ELT patterns, data modeling, and data warehousing.
  • Have used orchestration tools such as Apache Airflow or Azure Data Factory.
  • Know Infrastructure as Code tools, including Terraform.
  • Understand production systems, including observability, scalability, reliability, and performance.
  • Be able to lead technical initiatives independently from concept through delivery.
  • Communicate and collaborate effectively.
  • Have Upper-Intermediate or higher English proficiency.

Priekšrocības

  • Work remotely.

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