Senior Python Data Engineer

As a Senior Python Data Engineer with 4+ years of experience, you will play a crucial role in designing, building, and optimizing reliable data platforms and analytics solutions by partnering with product, analytics, and business teams. Your expertise in Azure Databricks, PySpark, Spark SQL, and Power BI will be essential in ensuring the success of our projects in a fast-paced and collaborative environment. **Key Responsibilities:** - Design and implement scalable ETL/ELT pipelines on Azure Databricks using PySpark/Spark SQL. - Model data for semantic layers to power BI and analytics use cases. - Build and maintain Power BI datasets, reports, and dashboards, utilizing DAX, data modeling, and Power Query. - Write, refactor, and optimize Python notebooks for transformation, feature engineering, and analysis. - Ensure data quality, accuracy, and consistency across reporting platforms by implementing validations and checks. - Automate data workflows and report refreshes using Python and Power BI. - Collaborate on data governance, security, and compliance practices within cloud environments. - Partner cross-functionally to translate business requirements into robust technical solutions. **Qualifications Required:** - 4+ years of software/data engineering experience with a strong emphasis on Python. - Expertise in PySpark (DataFrames/Datasets) and Spark SQL for building scalable pipelines. - Proven experience in creating interactive Power BI dashboards and reports. - Strong SQL skills including writing complex queries, performance tuning, and joining across multiple tables/views. - Familiarity with Azure services, especially Azure Data Lake and Azure Data Factory. - Solid understanding of data governance, data management, security, and compliance in cloud environments. - Track record of ensuring data integrity and reliability across analytics/BI layers. In addition to the required qualifications, it would be nice to have experience with Azure AI, Azure Copilot Studio, Azure Fabric, workflow automation using Power Automate, streaming ingestion with Azure Event Hubs or Apache Kafka, real-time data pipelines, familiarity with SDLC best practices, and Agile/Scrum delivery. If you join us, you can expect to work on high-impact, production-grade data platforms used across the business, have ownership, autonomy, and the opportunity to shape our data engineering standards, and be a part of a collaborative culture that values learning, craftsmanship, and measurable outcomes.,