Senior Data Engineer
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Main technologies
Additional skills
Experience
BRIDGEWISE
About the Project
Bridgewise is a technology research company using proprietary AI and language models to deliver instant fundamental analyses of global stocks to investors and financial institutions. The platform integrates directly into brokerage infrastructures, generating bespoke investment strategies and multi-language stock insights for millions of investors. The data engineering work supported the platform's ability to ingest, transform, and serve massive volumes of financial data reliably, with the governance and performance required for a regulated fintech environment.
- Fintech
- AI
- Machine Learning
Responsibilities
Designed and developed scalable system architectures for new services on the platform. Built and maintained ETL/ELT pipelines using AWS Glue and PySpark, processing large volumes of market and fundamental data. Architected a data lake on AWS S3 using Delta Lake for ACID reliability and data governance. Designed and optimized data models in PostgreSQL and DocumentDB for performance under production load. Handled deployment and ongoing back-end development. Worked across the full AWS stack including Athena, Glue, S3, Lambda, Step Functions, EC2, and ECS. Engagement lasted 12 months.
Skills & technologies
ESYNERGETICS
About the Project
Esynergetics provides an AI-powered infrastructure for secure document exchange between customers and suppliers, converting PDF-based documents into machine-readable formats. The platform delivers structured JSON representations of pdfs and images, integrates into existing document management processes of enterprise clients, and provides analytics on top of the extracted data. This phase of the work focused on core architecture and services, with a DevOps angle covering deployment and infrastructure.
- AI
- Machine Learning
- Management
Responsibilities
Designed and developed the core architecture, creating and implementing new services across the system. Handled deployment pipelines and ongoing back-end development. Took on knowledge sharing, mentorship, and code review responsibilities for the team. Worked on bug fixing across the codebase. The stack combined Python back-end (Django, FastAPI, aiohttp), OCR and data processing (OpenCV, Pandas, Tesseract), front-end and full-stack work (JavaScript, TypeScript, NodeJS, Angular), and AWS infrastructure (EC2, ECS, Route 53).
Skills & technologies
ESYNERGETICS
About the Project
Continuation of the Esynergetics platform, with a focus on the OCR invoice processing component. The team was responsible for extracting structured data from diverse invoice formats, which required continuous refinement of parsers, handling new document types, and integrating the OCR output into the broader data pipeline. This phase combined hands-on back-end development with team leadership responsibilities for the OCR group.
- Management
Responsibilities
Led the OCR team, handling knowledge sharing, mentorship, and project coordination. Implemented and maintained parsers, modifying the parser repetition logic for better reliability. Managed the OCR invoice processing workflow, including integration of new invoice types into the existing extraction system. Handled database queries and optimisation, fixed Docker configuration issues, and resolved bugs across the stack. Engagement lasted 14 months. The work required balancing individual contribution with team leadership responsibilities.