Key Responsibilities
Ingestion&Pipelines: Architect batchstream pipelines (Airflow Kafka dbt) for diverse structured and unstructured marked data. Provide reusable SDKs in Python and Go for internal data producers.
Storage&Modeling: Implement and tune S3 columnoriented and timeseries data storage for petabytescale analytics; own partitioning compression TTL versioning and cost optimisation.
Tooling & Libraries: Develop internal libraries for schema management data contracts validation and lineage; contribute to shared libraries and services for internal data consumers for research backtesting and real-time trading purposes.
Reliability & Observability: Embed monitoring alerting SLAs SLOs and CI/CD; champion automated testing data quality dashboards and incident runbooks.
Collaboration: Partner with Data Science QuantResearch Backend and DevOps to translate requirements into platform capabilities and evangelise best practices.
Qualifications :
Required Skills & Experience
7years building productiongrade data systems.
Familiarity with market data formats (e.g. MDP ITCH FIX proprietary exchange APIs) and market data providers.
Expertlevel Python (Go and C nice to have).
Handson with modern orchestration (Airflow) and event streams (Kafka).
Strong SQL proficiency: aggregations joins subqueries window functions (first last candle histogram) indexes query planning and optimization.
Designing highthroughput APIs (REST/gRPC) and data access libraries.
Strong Linux fundamentals containers (Docker) and cloud object storage (AWSS3 / GCS).
Proven track record of mentoring code reviews and driving engineering excellence.
Additional Information :
What we offer:
- Working in a modern international technology company without bureaucracy legacy systems or technical debt.
- Excellent opportunities for professional growth and self-realization.
- We work remotely from anywhere in the world with a flexible schedule.
- We offer compensation for health insurance sports activities and professional training.
Remote Work :
Yes
Employment Type :
Full-time
Key ResponsibilitiesIngestion&Pipelines: Architect batchstream pipelines (Airflow Kafka dbt) for diverse structured and unstructured marked data. Provide reusable SDKs in Python and Go for internal data producers.Storage&Modeling: Implement and tune S3 columnoriented and timeseries data storage for ...
Key Responsibilities
Ingestion&Pipelines: Architect batchstream pipelines (Airflow Kafka dbt) for diverse structured and unstructured marked data. Provide reusable SDKs in Python and Go for internal data producers.
Storage&Modeling: Implement and tune S3 columnoriented and timeseries data storage for petabytescale analytics; own partitioning compression TTL versioning and cost optimisation.
Tooling & Libraries: Develop internal libraries for schema management data contracts validation and lineage; contribute to shared libraries and services for internal data consumers for research backtesting and real-time trading purposes.
Reliability & Observability: Embed monitoring alerting SLAs SLOs and CI/CD; champion automated testing data quality dashboards and incident runbooks.
Collaboration: Partner with Data Science QuantResearch Backend and DevOps to translate requirements into platform capabilities and evangelise best practices.
Qualifications :
Required Skills & Experience
7years building productiongrade data systems.
Familiarity with market data formats (e.g. MDP ITCH FIX proprietary exchange APIs) and market data providers.
Expertlevel Python (Go and C nice to have).
Handson with modern orchestration (Airflow) and event streams (Kafka).
Strong SQL proficiency: aggregations joins subqueries window functions (first last candle histogram) indexes query planning and optimization.
Designing highthroughput APIs (REST/gRPC) and data access libraries.
Strong Linux fundamentals containers (Docker) and cloud object storage (AWSS3 / GCS).
Proven track record of mentoring code reviews and driving engineering excellence.
Additional Information :
What we offer:
- Working in a modern international technology company without bureaucracy legacy systems or technical debt.
- Excellent opportunities for professional growth and self-realization.
- We work remotely from anywhere in the world with a flexible schedule.
- We offer compensation for health insurance sports activities and professional training.
Remote Work :
Yes
Employment Type :
Full-time
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