Loading open roles
GirnarSoft
Python Data Engineering Architect - need application + data Architect combination on Python tech stack. Work involvements are building application dashboard using data from Datawarehouse. Which will involve application-level backend and front-end design and data layer design working on top of Datawarehouse.
GirnarSoft · posted 12 days ago
Bengaluru, Hyderabad +5 morerecruitment + vendor
About the role
| Python Data Engineering Architect - need application + data Architect combination on Python tech stack. Work involvements are building application dashboard using data from Datawarehouse. Which will involve application-level backend and front-end design and data layer design working on top of Datawarehouse. |
Python backend framework hands on work experience Fast API / Django
/ Flask.
Async I/O python library SQLAlchemy Core , Pydantic Backend Job systems Celery, Arq, or Dramatiq Working knowledge with any of the datawarehouse systems Snowflake, BigQuery, Redshift, Databricks, or ClickHouse Idea on performance optimization using columnar storage, partitioning and clustering strategies Pre-aggregation tables, materialized views, incremental refresh, approximate query engines Good to know DuckDB or Polars REST API / Graph QL cursor-based pagination for large result sets, streaming responses WebSocket or SSE patterns Caching architecture. Should have knowledge Infra and ops. Containerization, Kubernetes or ECS, CI/CD, observability |
| Python Data Engineering Architect - need application + data Architect combination on Python tech stack. Work involvements are building application dashboard using data from Datawarehouse. Which will involve application-level backend and front-end design and data layer design working on top of Datawarehouse. |
Python backend framework hands on work experience Fast API / Django
/ Flask.
Async I/O python library SQLAlchemy Core , Pydantic Backend Job systems Celery, Arq, or Dramatiq Working knowledge with any of the datawarehouse systems Snowflake, BigQuery, Redshift, Databricks, or ClickHouse Idea on performance optimization using columnar storage, partitioning and clustering strategies Pre-aggregation tables, materialized views, incremental refresh, approximate query engines Good to know DuckDB or Polars REST API / Graph QL cursor-based pagination for large result sets, streaming responses WebSocket or SSE patterns Caching architecture. Should have knowledge Infra and ops. Containerization, Kubernetes or ECS, CI/CD, observability |
Async I/O python library
SQLAlchemy Core , Pydantic
Backend Job systems Celery, Arq, or Dramatiq
Working knowledge with any of the datawarehouse systems Snowflake, BigQuery, Redshift, Databricks, or ClickHouse
Idea on performance optimization using columnar storage, partitioning and clustering strategies
Pre-aggregation tables, materialized views, incremental refresh, approximate query engines
Good to know DuckDB or Polars
REST API / Graph QL
cursor-based pagination for large result sets, streaming responses
WebSocket or SSE patterns
Caching architecture.
Should have knowledge Infra and ops. Containerization, Kubernetes or ECS, CI/CD, observability