Senior Software Engineer - Data Infrastructure
$202kUber
- *Senior Software Engineer - Data Infrastructure, Mobility Simulation and Planning**
- *About the role and team**
- **Build scalable data infrastructure:** Design and evolve shared feature stores and distributed processing pipelines that support model training, inference, backtesting, simulation, and planning.
- **Make data trustworthy:** Develop automated validation, monitoring, and alerting to detect freshness, completeness, and correctness issues before they affect downstream consumers.
- **Improve data lifecycle operations:** Build efficient capabilities for incremental processing, historical backfills, schema evolution, data versioning, and recovery from failed or incorrect writes.
- **Enable self-service:** Create reusable frameworks, APIs, and developer tooling that help engineers and scientists onboard features, investigate issues, and operate workflows with less manual support.
- **Optimize performance and cost:** Identify bottlenecks in data processing, storage, and orchestration, and improve throughput, resource efficiency, and reliability.
- **Drive technical projects end to end:** Translate ambiguous requirements into designs, lead implementation and rollout, and own production health through on-call, incident response, and long-term improvements.
- **Collaborate and mentor:** Partner with modeling, financial-data, and shared-platform teams to establish consistent data foundations; guide engineers through thoughtful design reviews, code reviews, and technical mentorship.
- 6+ years of professional experience in software engineering, data infrastructure, or a related technical role.
- Strong programming skills in Python, Java, Scala, Go, or a comparable language.
- Experience designing, building, and operating large-scale data pipelines or distributed data-processing systems.
- Strong SQL skills and experience with data modeling, storage systems, and query-performance optimization.
- Experience delivering technical projects from design through production rollout and ongoing operations.
- Ability to communicate technical tradeoffs and collaborate across engineering and data science teams.
- Bachelor’s or Master’s degree in Computer Science, Engineering, or equivalent practical experience.
- Experience with Apache Spark or comparable distributed data-processing frameworks.
- Experience with Apache Hudi or similar data lake technologies supporting incremental updates, schema evolution, and versioned datasets.
- Experience building feature stores or data infrastructure for machine learning, forecasting, optimization, or simulation.
- Experience developing reusable data-quality frameworks, observability systems, or tools for tracing and reconciling data across sources.
- Familiarity with workflow orchestration and distributed computing frameworks such as Ray.
- Experience building self-service platforms or automation that reduces operational overhead for engineers and scientists.
- A track record of measurable improvements in data reliability, processing performance, infrastructure cost, or developer productivity.
Vacancy posted 10 hours ago
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