Descrizione
Обязанности: Design, develop, and maintain ETL/ELT data pipelines for structured and semi‑structured data, Build and optimize data lakehouse solutions supporting analytics, reporting, and regulatory needs, Implement data ingestion from multiple sources (databases, APIs, files, messaging/ event streams), Perform data transformation, validation, and quality checks across end‑to‑end data flows, Collaborate with Business Analysts and stakeholders to translate requirements into data solutions, Support production environments, handle incident analysis, and contribute to performance optimization, Ensure compliance with data governance, security, and regulatory standards
Опыт: 3-5 YoE in Data Engineering with Databricks, Very strong Python, SQL, PySpark programming skills, Data Platforms: Databricks (Delta Lake, DLT), cloud data lakes / lakehouse architectures, Experience with Azure (ADLS, Data Factory, Synapse), or equivalent cloud services, Knowledge of Medallion architecture, dimensional models, Data Vault (nice to have), REST APIs, batch and streaming ingestion, Git, CI/CD pipelines, Azure DevOps or similar, Strong understanding of data quality, performance tuning, and scalability, Exposure to banking, risk, regulatory reporting, or analytics platforms, Experience supporting data‑intensive applications used for decision‑making and compliance, Very good English skills, Streaming technologies (Kafka, Event Hub), Experience with Power BI / Tableau for data consumption, Azure or Data
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