Senior Staff Data Engineer - Data & Services Team
N
NitrogenFinTech
United StatesFull-TimeStaff
Salary180000 - 200000 USD per year
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Job Details
- Experience
- 10+ years
- Required Skills
- PythonSQLKafkaSnowflakeTypeScriptAirflowGoRDBMSNosqldbtLangChain
Requirements
- 10+ years of hands-on experience in data engineering
- Expert at writing optimized SQL & Python
- Proficiency in Snowflake & dbt
- Deep experience designing reliable, production-grade data workflows
- Experience with CDC systems syncing data into and out of warehouses
- Experience building or integrating with APIs and services
- Worked with tools like DMS, OpenFlow, Airflow, Kafka, Debezium, S3
- Comfortable operating across both data pipelines and service-oriented systems
- Design scalable data and AI systems end-to-end
- Experience across RDBMS, data warehouses, NoSQL, and graph databases
- Experienced with modern AI architectures like agentic workflows, RAG, agent context & memory
- Worked with tools like MCP, LangChain and LangGraph
- Experience beyond core data tooling (backend services, APIs, full-stack systems)
- Experience with languages such as Go, TypeScript (strong plus)
- Deep technical expertise in how data engines and pipelines work
- Ability to troubleshoot difficult issues
- Actively leverage agentic AI developer tools (Claude Code, Devin, Cursor)
- Technical leadership and mentoring experience
Responsibilities
- Lead the design and evolution of the systems that move, transform, and expose data across our platform.
- Build and scale ingestion pipelines from external financial partners.
- Develop and maintain APIs and services that power those integrations.
- Shape the data layer that drives internal analytics and product experiences.
- Operate across the full lifecycle of data systems—from ingestion to consumption.
- Ensure data infrastructure is resilient, well-modeled, and built for long-term maintainability.
- Advance Nitrogen's data platform and service capabilities.
- Own the successful delivery of data flows end-to-end.
- Champion good data governance, industry best practices, and efficient processing techniques.
- Deliver high-quality, production-grade features, and reliably meet commitments.
- Set a high bar for technical productivity and efficiency through deep, consistent use of AI and agentic developer tools.
- Provide architectural leadership across data pipelines, APIs, and services.
- Develop a deep understanding of what our domain-specific data means to our customers.
- Proactively identify and address technical debt and developer experience gaps.
- Mentor and elevate the technical skills of fellow engineers.
- Demonstrate a continuous improvement mindset in both personal development and all technical workflows.
- Ensure technical contributions align with company objectives and expectations.
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