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Valtech
Valtech
5 001 – 10 000 Darbuotojai
H1B vizos rėmėjasKonsultavimasRinkodaraSaaS
„Valtech“ yra pasaulinė skaitmeninė agentūra, padedanti organizacijoms gerinti klientų patirtį ir plėtoti skaitmeninį verslą. Jos veikla apima technologijas, rinkodarą, duomenis ir dirbtinį intelektą, siekiant padėti įgyvendinti prekybos iniciatyvas, įmonių skaitmeninę transformaciją ir didinti rinkodaros efektyvumą. Visame pasaulyje veikiančios „Valtech“ komandos ir biurai bendradarbiauja su įmonėmis skaitmeninės strategijos, patirties inovacijų ir praktinio duomenų naudojimo srityse, kad padėtų kurti veiksmingesnę skaitmeninę ateitį.
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Darbai įmonėje

Senior Data Engineer, Bulgaria Remote

Build cloud data platforms and pipelines at Valtech to support analytics, AI, and data products. Work across AWS, Databricks, and other cloud environments, including GenAI use cases.

BGBulgarijaNuotolinisVisas etatasVyresnysis specialistasPrivaloma Kalba: anglųDuomenų inžinierius
AirflowApacheAWSAzureDebesijaGoogle Cloud PlatformKafkaPaskirstytosios sistemosPythonSparkSQLTerraformUnity

Aprašymas

  • Create and improve cloud data platforms for analytics, AI, and data products.
  • Build dependable batch, streaming, and near-real-time pipelines with Spark and Delta Lake.
  • Develop ingestion, transformation, and curation workflows for structured and unstructured data.
  • Apply lakehouse architecture and bronze, silver, and gold medallion layers.
  • Help migrate workloads between clouds, including re-platforming pipelines and data models.
  • Produce deployment-ready datasets for analytics, machine learning, causal modeling, and optimization.
  • Develop data pipelines for GenAI applications, including LLMs, RAG, vector data flows, and agent architectures.
  • Use Databricks MLflow, Unity Catalog, or comparable tools.
  • Create logical and physical data models.
  • Coordinate workflows with Databricks Workflows, Airflow, dbt, or equivalent tools.
  • Use event-driven and streaming architecture patterns.
  • Manage data governance, lineage, quality, and access controls with Unity Catalog, AWS Lake Formation, Microsoft Purview, GCP Dataplex, or similar tools.
  • Monitor data freshness, pipeline reliability, and SLA performance.
  • Provide data through APIs, feature inputs, and analytical endpoints.
  • Improve pipeline and infrastructure performance, scalability, and cost efficiency.
  • Clarify stakeholder needs, question requirements, and recommend alternatives.
  • Work with data scientists, ML engineers, analysts, platform teams, and business stakeholders.
  • Help teams adopt data products and contribute to shared practices.

Reikalavimai

  • Experience as a Senior Data Engineer.
  • Strong practical experience with Apache Spark and Delta Lake.
  • Strong Python and SQL skills.
  • Demonstrated experience building batch and streaming pipelines and production data platforms.
  • Solid knowledge of data modeling, data quality, and governance.
  • Substantial hands-on experience with the Databricks Lakehouse Platform.
  • Deep expertise in at least one major cloud: AWS, GCP, or Azure/Fabric.
  • Willingness and ability to work across cloud platforms.
  • Experience with lakehouse architectures and distributed systems.
  • Strong understanding of scalability, reliability, and performance.
  • Curiosity, problem-solving ability, and a collaborative approach to cross-functional work.
  • Comfort challenging business requirements.
  • Adaptability and interest in working across platforms.
  • Agile or consulting experience is beneficial.
  • Additional cloud experience or cloud migration experience is a plus.
  • Snowflake experience is a plus.
  • Experience with GenAI and AI data systems, including RAG pipelines, vector databases, and LLM data preparation, is a plus.
  • Experience with CI/CD for data pipelines and infrastructure as code, including Terraform and CloudFormation, is a plus.
  • Experience with streaming tools such as Kafka, Spark optimization, or ML and experimentation platforms is a plus.
  • Experience building data products or large-scale analytics platforms is a plus.

Privalumai

  • Flexible work arrangements, including hybrid options, and 25 vacation days.
  • Co-subsidized transportation and Multisport cards.
  • Premium health insurance for convenient access to healthcare services.
  • Funding for technical and other skills training, courses, and certifications.
  • A personal career development roadmap informed by performance reviews.
  • A self-care program with psychological consultations and team discussions.
  • A comfortable, productivity-focused office.
  • Team events and company gatherings.
  • Opportunities for professional growth.
  • A culture guided by shared values.
  • International career opportunities.
  • An inclusive culture with accessibility support.

Susiję darbai

Intetics

ML Data Engineer, Romania Remote

Intetics
501 – 1 000 Darbuotojai
KonsultavimasLogistikaSveikatos priežiūra
BGBulgarijaESIspanijaPLLenkijaPTPortugalijaRORumunijaSKSlovakijaNuotolinisVisas etatasVidutinis lygisVyresnysis specialistasPrivaloma Kalba: anglųDuomenų inžinierius
AWSEC2GoGraphQLgRPCIoTKafkaMongoDBPostgresPrometheusPulsarPythonSparkSQL

Build real-time, graph, and time-series data infrastructure for athlete performance. Support machine learning evaluation and AI systems for an Intetics customer in the United States.

Atidaryti