KAYALI BI Engineer

SummaryIntroduction of a new role to provide expertise across data warehousing platforms including Azure Data Bricks and Power BI along with all necessary integrations. The BI Engineer will be responsible for supporting, implementing, and maintaining data warehouse pipelines and reports to streamline business processes.ResponsibilitiesData Platform & ArchitectureManage a scalable modern Data platform leveraging the Azure ecosystem, including Azure Databricks, Azure Synapse Analytics, Azure Data Factory, and Azure Data Lake Storage.Design and implement Lakehouse architecture using Medallion (Bronze, Silver, Gold) patterns with Delta Lake to ensure data reliability, scalability, and performance with knowledge of Delta Lake and ACID‑compliant data architectures.Apply data modelling techniques (dimensional modelling, star/snowflake schemas) to support both operational and analytical use cases.Data Engineering & PipelinesDevelop and maintain robust, high‑performance data pipelines using cloud‑native technologies (Databricks, PySpark, Lakehouse Workflows) to support ingestion, transformation, and curation of large‑scale datasets.Identify and resolve complex data discrepancies across multi‑stage ETL/ELT pipelines, focusing on root‑cause analysis of failures, data skew, and late‑arriving data.Build and optimise end‑to‑end data integration frameworks, including ingestion from relational databases, flat files, and third‑party REST APIs (handling authentication, pagination, and incremental loads).Troubleshoot and resolve complex data pipeline failures, performance bottlenecks, and data inconsistencies, performing root‑cause analysis in production environments.Business Intelligence & Power BIDesign, develop, and optimise Power BI datasets, reports, and dashboards, applying best practices in data modelling, DAX, and performance tuning.Demonstrate high‑level proficiency in performance tuning and semantic model debugging, specifically using tools like DAX Studio and Tabular Editor to isolate issues within the filter context, row context, and complex relationship cardinalities.Strategically troubleshoot data issues and investigate Gateway connectivity failures, Direct Query latency issues, and visual‑level calculation errors to ensure report accuracy and faster response times for executive stakeholders.Data Integration & ConsumptionManage the integration of data platforms with Power BI, ensuring efficient data models and seamless data consumption for reporting and analytics.Data Governance & SecurityImplement and manage data security frameworks, including role‑based access control (RBAC), Row‑Level Security, and governance using Unity Catalog or equivalent tools.DevOps, CI/CD & DeploymentKnowledge of CI/CD pipelines using Azure DevOps or GitHub Actions to enable automated, reliable, and consistent deployment of data solutions.Performance Optimization & Cost ManagementMonitor and optimise data platform performance and cloud resource utilisation, identifying cost optimisation opportunities and ensuring efficient workload execution.Data Quality & ReliabilityImplement data quality, validation, and monitoring frameworks to ensure accuracy, consistency, and reliability of data assets.Stakeholder Collaboration & DeliveryCollaborate with cross‑functional teams including business stakeholders, analysts, and engineers to translate business requirements into scalable technical solutions.RequirementsMinimum 5+ years in both Reporting and Data engineering domain, with at least 3+ years focused on Azure‑based data platforms mainly Power BI and Azure Databricks.Comprehensive knowledge of the Azure Data Stack and strong hands‑on experience with Azure Databricks, Azure Data Lake Storage, Synapse, ADF and open‑source cloud native tools.Extensive experience in Power BI, including dataset design and optimisation, report and dashboard development using calculated measures, DAX etc.Knowledge of performance tuning techniques (query optimisation, import vs direct query, aggregations etc).Proficiency in SQL, PySpark, Python.Solid understanding of data modelling techniques.Effective problem‑solving skills backed by strong people skills.Excellent oral and written communication skills.#J-18808-Ljbffr