Business Area:
Sales Engineering
Seniority Level:
Mid-Senior level
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.
Are you passionate about making data and AI use cases accessible for enterprise clients?
Cloudera is seeking a customer-facing, hands-on Data Lakehouse Specialist to join our global team. 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 Business Intelligence (BI) and AI-ready analytics use cases. If you thrive on creative freedom and shaping the future of open data lakehouses and modern data warehousing at scale, we encourage you to apply.
Lead customer engagements by designing and presenting scalable, cloud-native lakehouse 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 self-serve BI, open table formats (Iceberg), and AI-ready data analytics.
Troubleshoot and resolve complex technical issues related to query performance, concurrent workload management, and data federation, providing guidance and leading escalations.
Drive internal and external technical enablement by exploring new analytical engines, developing educational materials, and sharing best practices around modern data warehousing.
Influence product roadmap by translating customer feedback and region-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 the open data lakehouse paradigm.
Collaborate effectively with cross-functional teams (Sales, Product, Engineering) to align on customer success and product vision.
Travel: Ability to travel to customer sites and Cloudera hubs approximately once per month.
Proven experience leading and implementing mission-critical data warehousing and BI use cases in industries such as Financial Services, Retail, Healthcare, Public Sector, etc.
Proven experience in designing, building, and deploying enterprise-grade data lakehouses and big data analytics platforms on cloud-native architectures.
Hands-on expertise with leading SQL engines, open table formats, and big data warehousing technologies, specifically Apache Iceberg, Trino, Apache Hive, and Apache Impala.
Strong background in architecting production data deployments across hybrid and multi-cloud environments, with specific expertise in massive-scale BI, ad-hoc analytics, and building an AI-ready data foundation.
Demonstrated ability to run Proofs of Concept (PoCs) and MVPs that lead to successful, enterprise-grade production deployments, ensuring high-concurrency query performance and cost optimization.
Practical experience in designing data-intensive architectures, including data modeling, navigating security, data quality, and the governance challenges required to serve trusted data to both analysts and data scientists.
Exceptional presentation skills, comfortable engaging with diverse audiences from SQL developers and data analysts to senior executives.
Ability to analyse customer data warehouse workloads and define technical migration or modernization roadmaps (e.g., from legacy appliances to an open data lakehouse) tailored to their specific needs.
Prior experience in pre-sales or technical consulting roles with a strong focus on big data, data warehousing, & AI platform solutions.
Direct experience with legacy or competing enterprise data warehouses (e.g., Snowflake, Google BigQuery, Amazon Redshift, Teradata) and advising customers/partners on migration strategies to open-source, cloud-native alternatives.
Experience with modern data modeling (e.g., dbt, Star Schema, Data Vault) and optimizing analytical query performance over distributed object storage.
Experience with, and interest in, open-source software and development practices.
Familiarity with Cloudera Data Warehouse (CDW), Cloudera Machine Learning (CML), and Shared Data Experience (SDX) for unified security and governance.
Relevant technical certifications (e.g., Snowflake SnowPro Core, AWS Certified Data Analytics, Google Cloud Professional Data Engineer).
Working knowledge of the broader open-source data and AI ecosystem, particularly integration points with data engineering pipelines (e.g., Apache Spark, Airflow).
Deep understanding of how structured, governed data in a lakehouse accelerates the adoption of machine learning, deep learning, and generative AI applications.
This role is not eligible for immigration sponsorship.
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
Employee Resource Groups
EEO/VEVRAA
#LI-Remote
#LI-MH2

Cloudera is the only data and AI platform company that brings AI to data anywhere: in clouds, data centers, and at the edge. Cloudera delivers 100% of data in all forms–whether it is in Cloudera or anywhere in the entire data estate. The world’s largest organizations rely on Cloudera to fuel insights that boost bottom lines, safeguard against threats, and save lives. Learn more at Cloudera.com.
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