Location: Remote (Must be located in EST Time Zone)
Experience: 5+ Years
Role Summary
We are seeking a hands-on Data Engineer with strong backend engineering expertise and experience working in financial services, analytics, or data-intensive environments. The ideal candidate will have deep knowledge of PostgreSQL, Python, AWS, FastAPI, and modern data engineering practices, along with experience supporting AI/RAG-based solutions. This is a highly execution-focused role involving ETL modernization, data architecture improvements, performance optimization, data quality initiatives, and operational excellence.
The candidate should be comfortable owning delivery, maintaining transparent project tracking, proactively managing risks, and communicating progress effectively with stakeholders.
Key Responsibilities
- Design, develop, and optimize scalable data pipelines, ETL workflows, and backend services.
- Refactor and modernize existing data engineering processes to improve performance, maintainability, and reliability.
- Perform extensive SQL optimization, data modeling, schema design, and PostgreSQL performance tuning.
- Build and maintain APIs and data services using Python and FastAPI.
- Develop and support cloud-native data solutions using AWS services and containerized environments.
- Implement data validation, reconciliation, testing, and quality assurance processes.
- Optimize Parquet-based storage, data processing, and query performance.
- Support AI and Retrieval-Augmented Generation (RAG) initiatives through data preparation and retrieval frameworks.
- Monitor data platform performance and proactively identify operational improvements.
- Maintain detailed task trackers, timelines, risks, dependencies, and status reports.
- Communicate project progress, blockers, and delivery updates to leadership and stakeholders.
- Collaborate with engineering, analytics, architecture, and business teams to deliver high-quality solutions.
Required Skills
- 5+ years of experience in Data Engineering, Backend Engineering, or related disciplines.
- Strong Python development experience.
- Hands-on experience with FastAPI and backend service development.
- Deep expertise in PostgreSQL, SQL optimization, indexing, partitioning, and performance tuning.
- Experience working with Parquet file formats and large-scale data processing.
- Strong knowledge of ETL/ELT design patterns and data engineering best practices.
- Experience with AWS services, preferably EKS, Lambda, S3, and cloud-native architectures.
- Strong understanding of API design, data services, and backend systems.
- Experience building scalable, production-grade data platforms.
- Excellent analytical, troubleshooting, and problem-solving skills.
- Strong communication skills with the ability to provide clear execution transparency and status reporting.
Required Domain Experience
- Experience working in Financial Services, Investment Management, Capital Markets, Banking, Analytics, or Data-driven business environments.
- Ability to understand complex business data flows and translate requirements into scalable engineering solutions.
AI / RAG Experience (Mandatory)
- Must have exposure to AI-powered solutions, Retrieval-Augmented Generation (RAG), vector search, semantic retrieval, or LLM-based applications.
- Please include specific AI/RAG project experience in candidate submissions.
Nice to Have
- Experience with Kubernetes and container orchestration.
- Experience with event-driven architectures and microservices.
- Exposure to data observability, lineage, and governance frameworks.
- Experience supporting analytics, reporting, or machine learning platforms.
- Familiarity with Agile delivery environments.
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