Key Responsibilities

- Own the metrics API

— a FastAPI service exposing tenant-scoped metrics over curated KPI data, including aggregation logic, query performance, and schema evolution

- Enforce multi-tenant isolation

— tenant and billing-entity scoping implemented structurally in the data access layer, not left to individual queries

- Design and evolve the data model

— SQLModel entities and Alembic migrations run safely against live data, with validation queries accompanying every schema change

- Own the API contract

— Pydantic models on the server matched by Zod schemas on the client, with no silent drift between the two

- Guarantee metric parity

— reconcile what the platform reports against the existing trusted BI numbers, and be able to prove and explain any figure that is questioned

- Tune performance

— caching strategy and invalidation, rate limiting, pagination over large result sets, and query plan analysis

- Implement authentication and authorization

— OAuth2 / OIDC integration, JWT validation, scopes and claims

- Build and review frontend work

— deliver React and TypeScript features to the team standard, review frontend pull requests, and take end-to-end ownership of a slice when the work calls for it

- Own quality

— pytest coverage on all logic that computes or scopes a number, plus tracing and structured logging sufficient to diagnose issues in production

- Support the application in production

— triage and resolve customer-raised issues across the stack, working from logs, traces, and metrics rather than guesswork

- Partner with data and analytics

— work with the data engineering and BI functions on metric definitions, mart design,



and reconciliation

Qualifications

- 6+ years building production backend services; 3+ years with Python in a modern async stack

- Working proficiency in TypeScript and React (required)

— able to build and review frontend features to the team standard.

- Deep FastAPI experience — async request handling, dependency injection, background tasks

- Robust PostgreSQL: async access via asyncpg, connection pooling, indexing, and the ability to read and fix a query plan

- Advanced SQL for analytics — window functions, CTEs, time-bucketed rollups, and correct handling of late-arriving and duplicate data

- SQLModel or SQLAlchemy, and Pydantic for modelling and validation

- Alembic migrations, including reversible migrations applied to live production data

- Multi-tenant application experience with row- or entity-level scoping and isolation guarantees

- OAuth2 / OIDC, JWT, and API authorization patterns

- Caching, rate limiting, and API performance tuning under real load
- pytest, async test patterns, fixtures, and testing against a real database rather than mocks

- Familiarity with reporting or analytics products, and comfort reasoning about whether a number is correct

- Git-based workflow, code review discipline, and CI/CD

- Cloud platform experience (Azure preferred), containerization, and production observability such as OpenTelemetry, Prometheus, or Loki is a plus

- Exposure to dbt, Snowflake, or warehouse-to-application data modelling is a plus

- Power BI or DAX literacy — enough to read a metric definition and reconcile against it — is a plus

- Strong written communication and the ability to work within defined overlap hours across time zones

📌 Full Stack Engineer (Hyderabad)
🏢 Anblicks
📍 Hyderabad