Enterprise Solution Engineer - Data & BI Platform
Location: <\/span><\/span><\/b>Austin, TX (in\-person at <\/span><\/span><\/span>979 Springdale Road, Suite 123, Austin, TX 78702) Type: <\/span><\/span><\/b>Full\-Time, In\-Office<\/span><\/span><\/span> As an Enterprise Pre\-Sales/ Solutions Engineer on our Data & Analytics Platform team, you will be the technical expert throughout the enterprise sales cycle; partnering with account executives and prospective customers to understand their business and technical objectives, lead discovery, and architect tailored solutions across the full data lifecycle, from ingestion and unification to analytics, activation, and AI. You will own the technical win.<\/span><\/span><\/span> You will become a trusted advisor and an expert across Zoho\u2019s data and analytics platform. You will use this expertise to map our capabilities to enterprise requirements, demonstrate our solutions at their best, and equip stakeholders, from analysts to C\-level executives, to make confident, well\-informed decisions, while sharing strategic recommendations and best practices.<\/span><\/span><\/span> This is a chance to join a growing team as one of the first U.S.\-based pre\-sales engineers focused on our data and analytics platform. The role is built for someone who can engage credibly at the enterprise level about an end\-to\-end platform \- not just dashboards \- navigate complex, multi\-stakeholder evaluations and proof\-of\-concepts, and who is energized by the shift toward agentic AI and wants to apply it in real, optimized customer environments. As the product line scales in the U.S., so will your opportunity for career growth and increased responsibility.<\/span><\/span><\/span> Serve as the technical expert in enterprise sales cycles, partnering with account executives to qualify opportunities, lead discovery, and drive the technical win for Zoho Analytics, DataPrep, and the wider data platform.<\/span><\/span><\/span> Lead solution architecture, proofs\-of\-concept (POCs), and pilots that span data sources, ingestion, the data lakehouse, unification, and downstream analysis and activation.<\/span><\/span><\/span> Build customized dashboards, reports, and data models that combine data from many enterprise applications and sources to demonstrate measurable business value.<\/span><\/span><\/span> Design semantic layers and a common object model, and demonstrate how unified business context drives trustworthy enterprise analytics and AI.<\/span><\/span><\/span> Showcase agentic AI capabilities \u2014 building, configuring, and demonstrating AI agents and AI\-assisted workflows that operate over governed, unified data.<\/span><\/span><\/span> Deliver tailored product demonstrations, technical workshops, and executive presentations that show our solutions in their best capacity.<\/span><\/span><\/span> Prepare and deliver compelling technical proposals and responses to RFPs, RFIs, and security questionnaires.<\/span><\/span><\/span> Address enterprise requirements around scalability, integration, and data governance, and act as a trusted technical advisor to customer stakeholders.<\/span><\/span><\/span> Provide internal enablement to sales and technical teams who need analytics, data\-engineering, or AI expertise, including how the data platform interacts with the broader Zoho ecosystem of business software.<\/span><\/span><\/span> Capture field and competitive insights and share them with product and R&D teams to influence the roadmap.<\/span><\/span><\/span> Working on onboarding sessions for new customers and serve as a bridge to our support engineers when clients need extra assistance.<\/span><\/span><\/span> Core Experience<\/i><\/span><\/span><\/b><\/span> <\/i><\/span> <\/span> Proven experience in an enterprise pre\-sales / solutions engineering, technical pre\-sales, or other senior, client\-facing technical role \u2014 ideally selling to or supporting enterprise accounts.<\/span><\/span><\/span> Previous experience in a data analyst, data engineering, or analytics\-engineering role, with a strong ability to interpret complex datasets, generate actionable insights, and communicate findings effectively.<\/span><\/span><\/span> Excellent communication and presentation skills, including product demos and presenting insights clearly through visualizations and dashboards, with the ability to explain complex technical and data concepts to non\-technical audiences and C\-level executives.<\/span><\/span><\/span> Comfort navigating complex, multi\-stakeholder enterprise evaluations, POCs, and procurement processes.<\/span><\/span><\/span> Good to have bachelor\u2019s degree in Computer Science or IT or a related field (or equivalent experience).<\/span><\/span><\/span> Data Platform & Engineering<\/i><\/span><\/span><\/b><\/span> <\/span> <\/span> Strong understanding of relational databases, data warehouses, and data lakehouse architectures, including integrating, manipulating, and modeling data from many sources.<\/span><\/span><\/span> Hands\-on experience building data pipelines and ETL/ELT processes using tools such as DataPrep, Alteryx, Talend, or dbt to prepare, cleanse, and enrich data.<\/span><\/span><\/span> Familiarity with multiple ingestion patterns like real\-time/streaming, batch, ETL, and zero\-copy \u2014 and with first\-party, third\-party, cloud, and on\-premise sources.<\/span><\/span><\/span> Experience designing semantic layers, common/shared data models, and reusable business context for analytics and AI.<\/span><\/span><\/span> Proficiency with programming languages such as Python and SQL.<\/span><\/span><\/span> Experience with BI and data platform products such as Zoho Analytics, Power BI, Tableau, Qlik, Snowflake, Google BigQuery, Amazon Redshift, Databricks<\/span><\/span><\/span> Ability to design and deploy reports and dashboards within a BI platform using data from a variety of sources.<\/span><\/span><\/span> AI & Agentic Tooling<\/i><\/span><\/span><\/b><\/span> <\/span> <\/span> Practical, hands\-on experience using modern AI and agentic tools, with the ability to apply them effectively in an optimized environment and go deep when needed.<\/span><\/span><\/span> Experience building, orchestrating, or demonstrating AI agents and AI\-assisted workflows \u2014 connecting them to data, APIs, MCPs and business actions.<\/span><\/span><\/span> Familiarity with data\-science and machine\-learning concepts such as regression, clustering, and classification, and how they enhance data analysis.<\/span><\/span><\/span> Bonus: <\/span><\/span><\/b><\/span>exposure to retrieval/vectorization, prompt design, and grounding AI on governed, unified data and a semantic layer.<\/span><\/span><\/span> Data Governance<\/i><\/span><\/span><\/b><\/span> <\/span> <\/span> Awareness of data governance fundamentals \u2014 role\-based access control, auditing, privacy, security, observability, and data cataloging \u2014 and the ability to speak to them with security\-conscious customers.<\/span><\/span><\/span> We are a private company with zero intention of going public. This gives us the freedom to chart our own course on product offerings, R&D priorities, and our authentic, humble, and diverse culture. If you are looking for stock options or an \u201cexit,\u201d you\u2019ll be disappointed.<\/span><\/span><\/span> We prefer long\-term employees and invest in our people to earn their loyalty. If you\u2019re looking for a short\-term gig, we discourage you from applying.<\/span><\/span><\/span>
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About the Role<\/span><\/span><\/b><\/span> <\/span> <\/span>
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What You\u2019ll Do<\/span><\/span><\/b><\/span> <\/span> <\/span>
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What We\u2019re Looking For:<\/span><\/span><\/b><\/span> <\/span> <\/span>
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Why You Should (or Shouldn\u2019t) Apply<\/span><\/span><\/b><\/span> <\/span> <\/span>
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