Day to Day: The Sr. Data Engineer is the one who designs and builds data foundations and end to end solutions for the business to maximize value from data. The role helps create a data-driven thinking within the organization, not just within IT teams, but also in the wider business stakeholder community. The Sr. Data engineer is expected to be a subject matter expert, who design & build data solutions and mentor junior engineers. They are also the key drivers to convert Vison and Data Strategy for IT solutions and deliver. Must Haves: • Proven hands-on experience with Azure Data Factory, Databricks, PySpark, DLT, and Unity Catalog • Hands on Databricks expertise including Structured Streaming, Performance Tunning & Cost Optimization • Strong command of SQL and data modelling concepts • Excellent communication and interpersonal skills • Ability to manage stakeholders and work collaboratively in a team environment • Self-motivated, proactive, and capable of working independently with minimal supervision • Strong problem-solving skills and a mindset focused on continuous improvement • Experience with multiple if not all of the following: Synapse, Stream Analytics, Glue, Airflow, Kinesis, Redshift, SonarQube, PyTest, Qlik Pluses: • Azure certifications (e.g., Azure Data Engineer Associate, Databricks Professional) • Experience with CI/CD pipelines and DevOps practices in data engineering • Familiarity with data governance and security best practices in Azure • Experience in project management, running a scrum team • Exposure to working with external technical ecosystem • MKDocs documentation experience Key Responsibilities: • Design, develop, and maintain scalable data pipelines using Azure Data Factory and Azure Databricks. • Implement data transformation workflows using PySpark and Delta Live Tables (DLT). • Manage and govern data assets using Unity Catalog. • Write efficient and optimized SQL queries for data extraction, transformation, and analysis. • Collaborate with cross-functional teams to understand data requirements and deliver high-quality solutions. • Demonstrate strong ownership and accountability in delivering end-to-end data solutions. • Communicate effectively with stakeholders to gather requirements, provide updates, and manage expectations.