Senior Data Engineer needed to develop scalable data solutions using Azure Databricks, Python, and SQL for a top financial client.
Responsibilities
Develop and maintain enterprise-grade data solutions in Azure Databricks, ADLS, ADF, Azure SQL, and Airflow. Automate data ingestion, transformation, notebook execution, and deployment activities. Collaborate with operations teams to ensure seamless integration of data pipelines and API services. Design, build, and support scalable data architectures capable of processing multi-millions of records daily. Lead technical initiatives and promote modern data engineering practices and reusable frameworks. Engage with stakeholders to interpret business needs, translate requirements, and implement solutions accordingly. Monitor system performance and implement improvements to enhance reliability and efficiency. Stay current with industry trends, emerging technologies, and best practices in cloud data engineering.
Requirements
7+ years of relevant experience in data engineering. Strong expertise in Azure Databricks, Python notebooks, and job orchestration. Proficient in SQL development and API service layer implementation. Deep hands-on experience with ADLS, ADF, Azure SQL, Airflow, Unity Catalog, and Lakeflow. Excellent communication, facilitation, and stakeholder management skills across technical and business teams. Ability to lead technical projects and influence best practices across teams.
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