Enterprise Solution Engineer - Data & BI Platform

About the role

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.

Responsibilities

• 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.
• Lead solution architecture, proofs-of-concept (POCs), and pilots that span data sources, ingestion, the data lakehouse, unification, and downstream analysis and activation.
• Build customized dashboards, reports, and data models that combine data from many enterprise applications and sources to demonstrate measurable business value.
• Design semantic layers and a common object model, and demonstrate how unified business context drives trustworthy enterprise analytics and AI.
• Showcase agentic AI capabilities — building, configuring, and demonstrating AI agents and AI-assisted workflows that operate over governed, unified data.
• Deliver tailored product demonstrations, technical workshops, and executive presentations that show our solutions in their best capacity.
• Prepare and deliver compelling technical proposals and responses to RFPs, RFIs, and security questionnaires.
• Address enterprise requirements around scalability, integration, and data governance, and act as a trusted technical advisor to customer stakeholders.
• 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.
• Capture field and competitive insights and share them with product and R&D teams to influence the roadmap.
• Work on onboarding sessions for new customers and serve as a bridge to our support engineers when clients need extra assistance.

Requirements

• Proven experience in an enterprise pre-sales / solutions engineering, technical pre-sales, or other senior, client-facing technical role — ideally selling to or supporting enterprise accounts.
• 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.
• 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.
• Comfort navigating complex, multi-stakeholder enterprise evaluations, POCs, and procurement processes.
• Good to have bachelor’s degree in Computer Science or IT or a related field (or equivalent experience).

Skills

• Strong understanding of relational databases, data warehouses, and data lakehouse architectures, including integrating, manipulating, and modeling data from many sources.
• 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.
• Familiarity with multiple ingestion patterns like real-time/streaming, batch, ETL, and zero-copy — and with first-party, third-party, cloud, and on-premise sources.
• Experience designing semantic layers, common/shared data models, and reusable business context for analytics and AI.
• Proficiency with programming languages such as Python and SQL.
• Experience with BI and data platform products such as Zoho Analytics, Power BI, Tableau, Qlik, Snowflake, Google BigQuery, Amazon Redshift, Databricks.
• 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.
• Experience building, orchestrating, or demonstrating AI agents and AI-assisted workflows — connecting them to data, APIs, MCPs and business actions.
• Familiarity with data-science and machine-learning concepts such as regression, clustering, and classification, and how they enhance data analysis.

Benefits

Commensurate with experience.

Pay

TBD

Schedule

TBD