Staff, DataEngineer

Position Title: Staff, Data Engineer Job Description: Roles & Responsibilities: Shape and drive enterprise-wide data architecture strategy: Define and evolve the long-term technical vision for scalable, resilient data infrastructure across multiple business units and domains. Lead large-scale, cross-functional initiatives: Architect and guide the implementation of data platforms and pipelines that enable analytics, AI/ML, and BI at an organizational scale. Pioneer advanced and forward-looking solutions: Introduce novel approaches in real-time processing, hybrid/multi-cloud, and AI/ML integration to transform how data is processed and leveraged across the enterprise. Mentor and develop senior technical leaders: Influence Principal Engineers, Engineering Managers, and other Staff Engineers; create a culture of deep technical excellence and innovation. Establish cross-org technical standards: Define and enforce best practices for data modeling, pipeline architecture, governance, and compliance at scale. Solve the most complex, ambiguous challenges: Tackle systemic issues in data scalability, interoperability, and performance that impact multiple teams or the enterprise as a whole. Serve as a strategic advisor to executive leadership: Provide technical insights to senior executives on data strategy, emerging technologies, and long-term investments. Represent the organization as a thought leader: Speak at industry events/conferences, publish thought leadership, contribute to open source and standards bodies, and lead partnerships with external research or academic institutions. Technical Skills 15+ years of experience Mastery of data architecture and distributed systems at enterprise scale: Deep experience in GCP . Advanced programming and infrastructure capabilities: Expertise inwriting database queries,Python, or Java, along with infrastructure-as-code tools like Terraform or Cloud Deployment Manager. Leadership in streaming and big data systems: Authority in tools such as BigQuery, Dataflow, Dataproc, Pub/sub for both batch and streaming workloads. Enterprise-grade governance and compliance expertise: Design and implement standards for data quality, lineage, security, privacy (e.g., GDPR, HIPAA), and auditability across the organization. Strategic integration with AI/ML ecosystems: Architect platforms that serve advanced analytics and AI workloads (Vertex AI, TFX, MLflow). Exceptional ability to influence across all levels: Communicate technical vision to engineers, influence strategic direction with executives, and drive alignment across diverse stakeholders. Recognized industry leader: Demonstrated track record through conference presentations, publications, open-source contributions, or standards development. Must Have Skills: Deep expertise in data architecture, distributed systems, andGCP. Python or Java, infrastructure-as-code (e.g. Terraform) Big data tools: BigQuery(Expert level. Having experience on performance tuning and UDFs), Dataflow, Dataproc, Pub/Sub (batch + streaming) Data governance, privacy, and compliance (e.g. GDPR, HIPAA) Data modeling and architecture - level expert, have experience on hybrid architectures SQL Skills level - Expert Deep understanding of BigQuery, have experience on partitioning, clustering and performance optimizations Experience on Cloud function, Composer and Cloud run, dataflow flex templates - should be able to write Understanding of full concepts of cloud architecture.