Quick Overview
Seniority
Mid Senior
Work mode
Hybrid
Location
New York, NY, United States
Posted
Yesterday
DockerSQLAWSETLSnowflakeJavaScriptKafkaKubernetesPostgreSQLPythonRedisdbt
Job Description
- MUST HAVE STRON PYTHON ENGINEERING AND FINANICAL BACKGROUND
- Build and maintain data pipelines ingesting from internal systems, market data vendors, and operational databases into analytical and application-facing stores
- Design and manage PostgreSQL and analytical data models that support front-office workflows and quantitative research
- Develop production Python and SQL code for ETL, validation, enrichment, and data quality monitoring
- Build and maintain lightweight internal applications and reporting interfaces, including browser-based tools using JavaScript where helpful
- Support research and analytics workflows involving large financial and time series datasets
- Partner with quantitative developers and investment users to improve data usability, transparency, and operational reliability
- 4+ years of experience in data engineering, analytics engineering, or software engineering with a strong data focus
- Strong Python experience required.
- Experience with relational databases; PostgresSql / Snowflake experience is a plus.
- Experience designing and operating ETL pipelines and data models in production
- Familiarity with dbt, AWS, Docker, Kubernetes (EKS), Kafka, Redis, and cloud data infrastructure is preferred
- Experience working with financial, transactional, or time series data is strongly preferred
- Some JavaScript experience for internal tools, dashboards, or data-grid-based interfaces is preferred
- Solid software engineering habits around testing, code quality, debugging, and documentation
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