Senior Data Engineer

Apply Description The Senior Data Engineer is responsible for designing, implementing, maintaining, and optimizing a cloud-based data architecture and data pipeline ecosystem. The position supports advanced analytics, machine learning operations, fraud detection initiatives, and investigative activities by delivering scalable, secure, and sustainable Azure-based data solutions. The Senior Data Engineer develops and maintains modern ELT/ETL pipelines, data models, source-controlled environments, and operational standards that enable efficient data ingestion, processing, storage, and access. Design, implement, and maintain scalable Azure-based data architecture supporting audits, investigations, and fraud analytics. Develop, optimize, and sustain ELT/ETL pipelines within Azure Synapse Analytics and Azure Machine Learning environments. Migrate and integrate large-scale datasets into Azure Data Lake Storage (ADLS). Establish source control, version management, and development standards across data engineering assets. Implement pipeline monitoring, validation, logging, and error-handling frameworks. Design and maintain data models, data dictionaries, entity relationship diagrams, and architectural documentation Optimize ingestion, transformation, storage, and retrieval performance across diverse data sources and formats. Develop self-service data access capabilities for analysts and investigators. Collaborate with Data Scientists to ensure infrastructure effectively supports machine learning and AI initiatives. Author and maintain Standard Operating Procedures (SOPs) governing data pipeline development, deployment, and monitoring. Evaluate emerging AI-enabled engineering tools and LLM-assisted automation capabilities. Recommend and implement architectural improvements that increase efficiency, reliability, security, and cost effectiveness. Requirements Bachelor's degree in Data Engineering, Computer Science, Data Science, Machine Learning, Mathematics, or related discipline; or 5 years of relevant applied experience. Five or more years of experience maintaining SQL database environments and performing advanced SQL/T-SQL operations. Five or more years of experience designing and maintaining cloud-based ELT/ETL solutions. Three or more years of experience working with Azure Synapse Analytics and Azure Machine Learning. Three or more years of experience developing data solutions using Python and Pandas. Experience supporting modern data platforms and cloud-native analytics architectures. Demonstrated expertise in data architecture design, pipeline optimization, and operational support.