Data Engineer

• Lead and guide the design and implementation of scalable streaming data pipelines
• Engineer and optimize real-time data solutions using frameworks like Apache Kafka, Flink, Spark Streaming
• Collaborate cross-functionally with product, analytics, and AI teams to ensure data is a strategic asset
• Advance ongoing modernization efforts, deepening adoption of event-driven architectures and cloud-native technologies
• Drive adoption of best practices in data governance, observability, and performance tuning for streaming workloads
• Embed data quality in processing pipelines by defining schema contracts, implementing transformation tests and data assertions, enforcing backward-compatible schema evolution, and automating checks for freshness, completeness, and accuracy across batch and streaming paths before production deployment
• Establish robust observability for data pipelines by implementing metrics, logging, and distributed tracing for streaming jobs, defining SLAs and SLOs for latency and throughput, and integrating alerting and dashboards to enable proactive monitoring and rapid incident response
• Foster a culture of quality through peer reviews, providing constructive feedback and seeking input on your own work

Principal Data Engineer

Lead Data Engineer

Manager, IT – Data Engineering

Scientific Data Engineer

Data Engineer

Cloud Data Engineer – Finance