Senior Data Engineer

This is a fully remote position, open to applicants in United States.

📋 Description

• The Senior Data Engineer is tasked with the design, implementation, maintenance, and optimization of a cloud-based data architecture and data pipeline ecosystem.

• This role 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 is responsible for developing and maintaining modern ELT/ETL pipelines, data models, source-controlled environments, and operational standards that facilitate efficient data ingestion, processing, storage, and access.

• Design, implement, and maintain scalable Azure-based data architecture that supports 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 various data sources and formats.

• Develop self-service data access capabilities for analysts and investigators.

• Collaborate with Data Scientists to ensure that infrastructure effectively supports machine learning and AI initiatives.

• Author and maintain Standard Operating Procedures (SOPs) that govern data pipeline development, deployment, and monitoring.

• Evaluate emerging AI-enabled engineering tools and LLM-assisted automation capabilities.

• Recommend and implement architectural enhancements that improve efficiency, reliability, security, and cost-effectiveness.

⛳️ Requirements

• A Bachelor's degree in Data Engineering, Computer Science, Data Science, Machine Learning, Mathematics, or a related field; or 5 years of relevant applied experience.

• At least five years of experience in maintaining SQL database environments and performing advanced SQL/T-SQL operations.

• A minimum of five years of experience in 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 in developing data solutions using Python and Pandas.

• Experience in supporting modern data platforms and cloud-native analytics architectures.

• Proven expertise in data architecture design, pipeline optimization, and operational support.

🏝️ Benefits

• Health insurance

• 401(k) matching

• Flexible work hours

• Paid time off

• Remote work options