[Hiring] Senior Field Specialist - Data Engineering & Streaming @Cloudera

Role Description

At Cloudera, we empower people to transform complex data into clear and actionable insights. With as much data under management as the hyperscalers, we're the preferred data partner for the top companies in almost every industry. Powered by the relentless innovation of the open source community, Cloudera advances digital transformation for the world’s largest enterprises.

Cloudera is seeking a pre-sales customer-facing, hands-on Data Engineering & Streaming Specialist to join our team in the US. In this pivotal role, you'll leverage your deep technical expertise to empower our customers, influence product direction, and drive success across our most impactful data engineering, real-time streaming, and AI readiness use cases. If you thrive on creative freedom and shaping the future of cloud-native data architectures and AI at scale, we encourage you to apply.

As a Data Engineering & Streaming Specialist, You Will:

• Lead customer engagements by designing and presenting scalable, cloud-native data engineering architectures and business outcomes to technical and executive stakeholders.
• Provide deep domain expertise throughout the sales cycle, supporting PoCs, solution sizing, and adoption for new and existing customers focusing on data prep, CDC, streaming use cases, and AI readiness.
• Troubleshoot and resolve complex technical issues in data pipelines, providing guidance and leading escalations to ensure customer success.
• Drive internal and external technical enablement by exploring new cloud-native streaming and batch technologies, developing educational materials, and sharing best practices.
• Influence product roadmap by translating customer feedback and EMEA-specific requirements into actionable insights for our product and engineering teams.
• Act as a Cloudera evangelist, participating in community activities, speaking at events, and contributing to knowledge sharing around modern, AI-ready data engineering.
• Collaborate effectively with cross-functional teams (Sales, Product, Engineering) to align on customer success and product vision.

Qualifications

• Proven experience leading and implementing mission-critical data use cases in industries such as Financial Services, Retail, Healthcare, Public Sector, etc.
• Proven experience in designing, building, and deploying enterprise-grade data engineering pipelines and real-time streaming solutions on modern, cloud-native data architectures.
• Hands-on expertise with leading data processing and streaming technologies, specifically Apache Spark, Airflow, Apache NiFi, Apache Flink, and Apache Kafka.
• Strong background in architecting production data deployments across hybrid and multi-cloud environments, with specific expertise in data preparation, Change Data Capture (CDC), and data ingestion at massive scale.
• Demonstrated ability to run Proofs of Concept (PoCs) and MVPs that lead to successful, enterprise-grade production deployments, ensuring data pipelines are optimized for AI readiness.
• Practical experience in designing and implementing data-intensive use cases, including navigating the associated security, data quality, and governance challenges required to build an AI-ready data foundation.
• Exceptional presentation skills, comfortable engaging with diverse audiences from data engineers to senior executives.
• Ability to analyse customer data workloads and define technical migration or modernization roadmaps tailored to their specific needs.

Requirements

• Prior experience in pre-sales or technical consulting roles with a strong focus on big data & AI platform solutions.
• Direct experience with legacy or competing streaming/data engineering platforms (e.g., Confluent, Databricks, AWS EMR/Glue) and advising customers/partners on migration strategies to cloud-native alternatives.
• Experience with DataOps, including CI/CD for data pipelines and automated data quality frameworks essential for trusted AI.
• Experience with, and interest in, open-source software and development practices.
• Familiarity with Cloudera's Data Engineering (CDE) and DataFlow (CDF) components, as well as Shared Data Experience (SDX).
• Relevant technical certifications (e.g., Databricks Certified Data Engineer, Confluent Certified Developer, AWS Certified Data Analytics).
• Working knowledge of the broader open-source data and AI ecosystem, particularly open table formats that drive cloud-native architectures (e.g., Apache Iceberg) and container orchestration (Kubernetes).
• Deep understanding of the data engineering prerequisites required for machine learning, deep learning, and generative AI applications.

Benefits

• Generous PTO Policy
• Support work life balance with Unplugged Days
• Flexible WFH Policy
• Mental & Physical Wellness programs
• Phone and Internet Reimbursement program
• Access to Continued Career Development
• Comprehensive Benefits and Competitive Packages
• Paid Volunteer Time
• Employee Resource Groups