Senior Data Engineer

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.