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Sedona Digital
Sedona Digital
51 – 200 Zaposleni
LogistikaSvetovanjeZdravstveno varstvo
Sedona Digital je tehnološko svetovalno podjetje, usmerjeno v procese, ki nudi storitve organizacijam v panogah, vključno z zdravstvom in logistiko. Njegovo delo obsega tehnološko strategijo, podatkovno arhitekturo in inženiring, umetno inteligenco in napovedno analitiko, razvoj programskih izdelkov, posodabljanje aplikacij, selitev v oblak, upravljane storitve Azure, DevOps in CI/CD. Podjetje podpira tudi varnost v oblaku, upravljane operacije SOC in stalno zagotavljanje skladnosti ter podjetjem pomaga graditi, upravljati in varovati tehnološka okolja, ki temeljijo na podatkih in so zasnovana za oblak.
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Delovna mesta v podjetju

Senior Data Engineer, Romania Remote | Sedona Digital

Build and support PySpark, SQL, and Databricks data platforms for Sedona Digital’s insurance-sector clients. Work on pipelines, reconciliation, data quality, and cloud data solutions.

RORomunijaRSSrbijaNa daljavoPolni delovni časSeniorZahtevani Jezik: angleščinaPodatkovni inženir
Google Cloud PlatformPySparkSQL

Opis

  • Evaluate and rebuild ingestion pipelines for operational and source-system data.
  • Design data mappings, lineage, dependencies, and controlled migration and cutover plans.
  • Create and maintain detailed data reconciliation processes.
  • Improve PySpark data processing and hierarchy and roll-up capabilities.
  • Add testing, versioning, metadata, observability, and deployment controls.
  • Work with business and technical specialists to improve data coverage.
  • Evaluate GCP data pipeline options and help implement them.
  • Explore sourcing mappings and reference data directly from systems such as Microsoft Dynamics 365.
  • Support changes to reporting hierarchies and filtering logic, including impact assessment, testing, and reconciliation.
  • Create and maintain automated data-quality checks, monitoring, and operational controls.
  • Help teams adopt centralised reporting and data capabilities.
  • Prepare technical documentation, decision records, reconciliation evidence, variance explanations, and handover materials.
  • Deliver work through a prioritised backlog and short iterative sprints with engineers and stakeholders.

Zahteve

  • At least five years of professional experience in data engineering or a closely related data role, including substantial hands-on work building and supporting production data solutions.
  • Strong practical experience with PySpark, SQL, and Databricks, including developing and supporting production-grade data pipelines.
  • Hands-on experience with GCP data technologies and pipelines.
  • Experience testing and optimising data pipelines and supporting their operation.
  • Strong experience modelling dimensional, master/reference, or hierarchical data.
  • Experience implementing complex entity matching, data mappings, and roll-up logic with appropriate traceability.
  • Practical experience implementing automated data-quality checks and reconciliation processes.
  • Experience with observability, audit history, version control, and CI/CD in data engineering solutions.
  • Experience assessing source-system data and documenting data contracts, mappings, lineage, and dependencies.
  • Experience managing controlled data pipeline or platform transitions.
  • Ability to investigate data issues and explain differences in values, record counts, mappings, and hierarchy outcomes clearly.
  • Ability to work directly with platform teams, analysts, and business specialists, turning ambiguous reporting and mapping needs into tested engineering solutions.
  • Strong communication skills and the ability to prepare concise technical documentation, decision records, variance explanations, and handover materials.
  • Self-directed and comfortable working in a collaborative, iterative delivery environment.
  • Preferred: Experience in insurance, the London Market, reinsurance, brokerage, distribution, or policy-level data environments.
  • Preferred: Experience integrating Microsoft Dynamics 365 or similar operational source systems.
  • Preferred: Experience with Power BI, including semantic models and reporting dependencies.
  • Preferred: Experience with Slowly Changing Dimensions (SCDs) and historical hierarchy management.
  • Preferred: Experience supporting complex master/reference data, entity matching, and hierarchy solutions.
  • Preferred: Experience investigating historical data and reporting discrepancies.
  • Preferred: Experience supporting controlled data migrations, source-system transitions, or platform changes.
  • Preferred: Experience in distributed Agile teams and collaborating with UK-based business and technical stakeholders.

Sorodna delovna mesta

Intetics

ML Data Engineer, Romania Remote

Intetics
501 – 1000 Zaposleni
LogistikaSvetovanjeZdravstveno varstvo
BGBolgarijaESŠpanijaPLPoljskaPTPortugalskaRORomunijaSKSlovaškaNa daljavoPolni delovni časSrednja ravenSeniorZahtevani Jezik: angleščinaPodatkovni inženir
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.

Odpri