Data Engineering & Streaming Specialist

Business Area: Sales Engineering

Seniority Level: Mid-Senior level

Job 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 customer-facing, hands-on Data Engineering & Streaming Specialist to join our global team. In this pivotal role, you will leverage deep technical expertise to empower our enterprise 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, customer engagement, and shaping the future of cloud-native data architectures and AI at scale, this role provides the platform to make a global impact.

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 both technical and executive stakeholders.
• Provide deep domain expertise throughout the sales cycle, supporting Proof of Concepts (PoCs), solution sizing, and platform adoption focused on data prep, Change Data Capture (CDC), streaming, and AI readiness.
• Troubleshoot and resolve complex technical issues in customer data pipelines, providing architectural guidance and leading technical escalations.
• Drive internal and external technical enablement by exploring new cloud-native streaming and batch technologies, developing educational materials, and sharing best practices.
• Influence the product roadmap by translating customer feedback and regional requirements into actionable insights for Product and Engineering teams.
• Act as a Cloudera evangelist, participating in open-source community activities, speaking at industry events, and sharing expertise on modern, AI-ready data engineering.
• Collaborate effectively across Sales, Product, and Engineering teams to align customer outcomes with product vision.
• Strong English

We’re excited about you if you have:

• Proven experience leading and implementing mission-critical data use cases in enterprise environments (e.g., Financial Services, Retail, Healthcare, Public Sector).
• Extensive experience designing, building, and deploying enterprise-grade data engineering pipelines and real-time streaming solutions on modern, cloud-native architectures.
• Hands-on expertise with core processing and streaming technologies, specifically Apache Spark, Airflow, Apache NiFi, Apache Flink, and Apache Kafka.
• Strong background in architecting production deployments across hybrid and multi-cloud environments, focusing on data preparation, Change Data Capture (CDC), and ingestion at scale.
• Demonstrated ability to run PoCs and MVPs that transition into successful, production-grade deployments optimized for AI readiness.
• Practical experience navigating enterprise security, data quality, and governance challenges to build reliable data foundations.
• Exceptional communication and presentation skills, with comfortable engagement spanning data engineers to executive leadership.
• Experience analyzing customer data workloads to define tailored technical migration or modernization roadmaps.
• Working knowledge of the broader open-source data and AI ecosystem, particularly open table formats like Apache Iceberg and container orchestration via Kubernetes.

You may also have:

• Prior experience in pre-sales, solutions architecture, or technical consulting roles focused on Big Data & AI platform solutions.
• Direct experience with legacy or competing streaming/data engineering platforms (e.g., Confluent, Databricks, AWS EMR/Glue) and leading migration strategies to cloud-native alternatives.
• Experience with DataOps practices, including CI/CD for data pipelines and automated data quality frameworks.
• Direct familiarity with Cloudera components such as Cloudera Data Engineering (CDE), Cloudera DataFlow (CDF), and Shared Data Experience (SDX).
• Relevant technical certifications (e.g., Databricks Certified Data Engineer, Confluent Certified Developer, AWS Certified Data Analytics).
• Deep understanding of data engineering prerequisites for machine learning, deep learning, and Generative AI applications.

What you can expect from us:

• 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

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