Sales Engineer

📋 Description

• Qualification of leads: Initiates first contact and performs thorough evaluations of leads to determine if the potential client has a genuine need, capability, and readiness to implement Data & AI solutions;

• Needs assessment and diagnosis: Analyzes and comprehends the client's business challenges and goals, pinpointing how data- and AI-driven solutions can create value, enhance processes, or address specific issues;

• Solution development: Collaborates with the sales team, architects, and engineers to create an initial technical solution that aligns with the client's needs. This may include defining data architecture, selecting AI models, and planning integrations;

• Demonstrations and presentations: Prepares and delivers tailored, compelling demonstrations that illustrate the practical applications and advantages of Data & AI solutions for the client. It is crucial to convey complex technical ideas in straightforward language focused on business outcomes;

• Proof-of-concept (PoC) development: In certain situations, the pre-sales expert may lead or assist in developing proofs of concept to confirm the technical viability of the solution and showcase its potential value prior to engagement;

• Sales assistance: Aids the sales team by providing technical information, case studies, and commercial proposals, ensuring that the solution's value and features are communicated precisely and strategically;

• Market and trend analysis: Stays informed about market trends, innovations in Data & AI, and competitor offerings to ensure the company's solutions remain competitive and relevant.

⛳️ Requirements

• Technical skills in cloud and data:

• Strong expertise in cloud platforms (AWS, GCP, Azure);

• Proficient in data technologies such as Snowflake, Databricks, and DBT;

• Experience in constructing and architecting data solutions (Data Lakes, Data Warehouses, data pipelines).

• Experience in engineering and architecture:

• Proven experience as a data engineer or data architect, with a background in complex, large-scale projects;

• Familiarity with DataOps best practices, security, and performance optimization.

• Consultative mindset:

• Ability to collaborate with clients to identify and prioritize use cases that deliver business value;

• Proficiency in translating technology into business advantages and showcasing return on investment (ROI).

• Knowledge of AI:

• Understanding of concepts, frameworks, and applications within Artificial Intelligence and Machine Learning;

• Experience in applying AI solutions to resolve specific client business challenges.

🏝️ Benefits

• Position also open to candidates with disabilities