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Mid-level generalist data engineer role at a known bank, multiple common skill requirements.
Technical data engineering skills are transferable, but banking KPI familiarity raises domain specificity.
Explicit 5–10 years and mandatory Fabric/Databricks/Power BI/Python skills enforce strict filters.
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Lead data sourcing, ingestion, and transformation pipelines using Microsoft Fabric and Databricks, including managing bronze, silver, and gold data layers.
Design, develop, and maintain semantic models and Power BI dashboards aligned with business requirements and enterprise standards, ensuring performance and governance.
Enable self-service analytics and AI-driven insights by creating playbooks, documentation, and supporting conversational analytics within the data domain.
5-10 years of relevant experience as Data Engineer and Analyst.
Strong technical skills in Microsoft Fabric, Spark (PySpark preferred), Python, SQL, and Power BI with experience in data warehousing, modeling, and visualization.
Bachelor's or Master's degree in Computer Science or Engineering.
Experience developing or supporting executive-level reporting and maintaining high-quality documentation; familiarity with Agile and data governance frameworks.
Experienced in building or contributing to frameworks, templates, or shared semantic models with a strong product mindset and engineering rigor.
Demonstrated ability to translate complex business requirements into technical data design and analytical solutions in enterprise-scale or regulated environments.
Comfortable working with legacy BI modernization, complex DAX calculations, and enabling governed self-service analytics with a focus on performance and metric consistency.