Senior Data Engineer, Databricks Migration
Sigma Software GroupMigrate enterprise retail analytics from BigQuery to Databricks Lakehouse, building scalable PySpark pipelines, medallion architecture, and governed cloud data platforms.
Atvērt
Sedona Digital ir uz procesiem balstīts tehnoloģiju konsultāciju uzņēmums, kas apkalpo organizācijas dažādās nozarēs, tostarp veselības aprūpē un loģistikā. Uzņēmuma darbība aptver tehnoloģiju stratēģiju, datu arhitektūru un inženieriju, mākslīgo intelektu un prognozējošo analītiku, programmatūras produktu izstrādi, lietojumprogrammu modernizāciju, migrāciju uz mākoni, Azure pārvaldītos pakalpojumus, DevOps un CI/CD. Uzņēmums nodrošina arī mākoņa drošību, pārvaldītas SOC darbības un nepārtrauktu atbilstības nodrošināšanu, palīdzot uzņēmumiem veidot, pārvaldīt un aizsargāt uz datiem balstītas, mākoņdatošanai pielāgotas tehnoloģiju vides.
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.
Apraksts
- 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.
Prasības
- 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.
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