Build dependable data collection and storage for financial applications: consuming REST and WebSocket APIs, validating data, and orchestrating pipelines into PostgreSQL.
Duration6 weeks
LevelIntermediate
Modules6
Lessons24
This course teaches the engineering needed to move financial data from external APIs into well-modeled, trustworthy storage. You will consume REST and streaming APIs safely, handle authentication, pagination, rate limits and retries, and design schemas for time series and reference data in PostgreSQL. You will then validate, schedule and monitor pipelines and expose clean data through your own FastAPI service.
6 modules · 24 lessons · 6 weeks. Curriculum preview; the final syllabus may change before enrollment opens.
Build an ingestion service that pulls daily bars from a public or mock API into PostgreSQL with backfill and deduplication
Implement a WebSocket consumer that buffers streaming quotes, validates them and writes batches to storage
Publish a FastAPI service that serves cleaned bars and reference data with OpenAPI documentation and tests
Quantzivo certificates are completion credentials issued by Quantzivo, not accredited qualifications. Courses teach technical and research skills; they do not promise investment returns or provide investment advice.
5 weeks5 modulesLearn the foundations of financial data engineering: data types, schemas, SQL, ingestion, cleaning, corporate actions and reliable batch pipelines in Python.
7 weeks7 modulesBuild batch and streaming market data pipelines in Python with Kafka, PostgreSQL and Parquet, covering normalization, bar aggregation, quality checks and replay.
8 weeks8 modulesDesign reliable financial backends: ledger data models, idempotent APIs, event-driven processing with Kafka, security, observability and audit trails.
Reserve your place in a few steps, or ask us anything about the curriculum, schedule and format first.
