Sr. Staff Engineer, Data Engineering

About the role

We are seeking skilled engineers to build scalable distributed systems and integrate agentic AI and conversational analytics. As a Senior Staff Engineer you will lead the architecture, data modeling, and core infrastructure powering our next‑generation AI and analytics platforms.

Key responsibilities

• Architect, develop, and deploy global‑scale distributed platforms and pipelines for massive data ingestion, transformation, and analytical reporting.
• Design and refine backend infrastructure that supports Agentic AI workflows, autonomous systems, and conversational analytics with natural‑language interfaces.
• Partner with application teams to define data strategies and durable conceptual models spanning OLTP/OLAP and generative AI architectures (e.g., RAG).
• Evaluate data integration challenges and deliver optimized architectural solutions for complex business requirements.
• Research emerging AI techniques and advanced machine‑learning methodologies to continuously enhance data design patterns.
• Provide technical leadership and mentorship across the project lifecycle, focusing on efficient data modeling, prompt engineering, and high‑performance data access services.

Required profile

• At least 8 years of hands‑on experience in architecture, design, or development of enterprise data solutions, applications, and integrations.
• Proven experience designing and deploying Agentic AI systems and working with AI application frameworks.
• Strong communication and presentation skills with the ability to articulate complex concepts clearly.
• Bachelor’s or Master’s degree in a STEM discipline.

Required skills

• Python (preferred), Java, Scala
• SQL and familiarity with semantic search / Natural Language‑to‑SQL paradigms
• Relational databases: PostgreSQL, MySQL, Oracle
• Columnar/NoSQL/Vector stores: StarRocks, ClickHouse, BigQuery, Pinecone, pgVector
• Distributed processing engines: Apache Spark, Apache Flink
• Distributed queues: Apache Kafka, AWS Kinesis, GCP Pub/Sub
• Software‑engineering best practices: unit testing, code reviews, design documentation
• Cloud platforms: Google Cloud Platform, Azure, Amazon Web Services