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We are seeking a highly skilled Data Engineer with strong backend engineering expertise and solid finance/analytics domain knowledge. This role is focused on building, optimizing, and maintaining scalable data pipelines, improving data architecture, enhancing operational reliability, and driving data quality initiatives. The ideal candidate will have extensive experience with Python, PostgreSQL, AWS services, and modern data engineering practices, along with exposure to AI/RAG-based solutions. Contract Duration: 6+ Months Rate Range: $50-60/hr on W2
Job Responsibility
Design, develop, optimize, and maintain scalable data pipelines and ETL/ELT workflows
Refactor and enhance existing data processing frameworks to improve performance and reliability
Perform extensive data validation, testing, and quality assurance across data platforms
Optimize SQL queries, database structures, and table performance within PostgreSQL environments
Implement and support backend services and APIs using Python and FastAPI
Develop and maintain data solutions leveraging AWS services including EKS and Lambda
Work with Parquet files and large-scale datasets to support analytics and reporting requirements
Improve overall data architecture, operational stability, and system performance
Maintain detailed task tracking, status reporting, and execution transparency through Excel-based project tracking
Proactively identify risks, communicate project status, and manage timelines effectively
Collaborate with business, analytics, and engineering teams to support data-driven initiatives
Contribute to AI and Retrieval-Augmented Generation (RAG) use cases and data integrations
Requirements
6+ years of experience in Data Engineering, Backend Engineering, or related roles
Strong hands-on experience with Python development
Extensive experience with PostgreSQL and advanced SQL optimization
Experience building and maintaining ETL/ELT pipelines and data integration workflows
Strong knowledge of data engineering concepts, data modeling, and data architecture
Experience working with Parquet file formats and large-scale datasets
Hands-on experience with AWS services including EKS, Lambda, and cloud-native architectures
Experience developing APIs and microservices using FastAPI or similar frameworks
Strong data testing, validation, troubleshooting, and performance tuning skills
Excellent organizational skills with the ability to manage timelines, priorities, and status reporting
Strong communication skills and ability to work independently in a remote environment
Must be located within the EST time zone
Nice to have
Experience within financial services, investment management, analytics, or related domains
Experience with AI solutions and Retrieval-Augmented Generation (RAG) frameworks
Familiarity with machine learning data pipelines and AI-powered applications
Experience working in highly data-intensive environments
Strong understanding of operational monitoring and reliability practices