Senior Software Engineer, Data Platform
Senior Software Engineer building and operating broad data platform infrastructure for data, analytics, ML, AI, and agent workflows. Requires 5+ years of software engineering experience with distributed systems, production data platforms, cloud infrastructure, and systems design.
About the job
Responsibilities
- Design, build, and operate infrastructure for reliable, scalable, and cost-effective data, analytics, ML, and AI workflows.
- Build reusable workflow and integration capabilities for moving, processing, and using data across platforms.
- Build data-access and query capabilities across warehouses, lakehouses, and operational systems.
- Develop platform capabilities for research, analytics, and long-running agent workflows, including orchestration, state management, retries, evaluation, observability, and result delivery.
- Strengthen data security through least-privilege access, short-lived service identities, data masking, and audit controls.
- Improve platform reliability, data quality, performance, cost, observability, and developer experience.
- Lead projects from technical design through production operation, including incident response and long-term improvements.
- Partner with product, engineering, data science, and business teams to develop durable platform capabilities.
- Help set technical direction and raise engineering standards.
Requirements
- 5+ years of software engineering experience building backend systems, distributed systems, infrastructure, or data platforms.
- Proven record of owning and delivering complex technical projects.
- Strong hands-on coding skills in a backend or systems language.
- Experience with production data platforms, including data warehouses, distributed-query systems, lakehouse storage and compute, workflow orchestration, cloud infrastructure, and infrastructure as code.
- Experience building integrations and data-access systems that move or expose data across platforms.
- Experience owning production systems, including reliability, security, observability, cost, and incident response.
- Strong systems-design skills and judgment across reliability, security, scale, cost, and usability.
- Ability to work across multiple technical areas and make progress through ambiguity.
- Strong communication skills with technical and non-technical partners.
Nice to Have
- Experience building ML platform capabilities or training, deploying, and operating ML models in production.
- Experience building agent platforms, long-running agent workflows, or similar distributed asynchronous systems.
- Experience with ML or agent evaluation and observability.
- Experience with data discovery, lineage, access controls, or governance systems.
Compensation
- US-based salary range: $168,000–$280,000 annually, plus benefits and equity.
Skills
Python, Snowflake, Databricks, Starrocks, Apache Iceberg, Delta Lake, Spark, AWS, Kubernetes, Infrastructure As Code, Dagster, Apache Airflow, Prefect, MLflow, Langsmith
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