Presales Technical Consultant / Solution Architect

About the Role

We are looking for a Presales Technical Consultant - Big Data & Databricks who combines strong technical expertise in modern data platforms with excellent client-facing and presales capabilities.

In this role, you will serve as a key technical bridge between our sales teams, global clients, and delivery organizations. You will lead the technical aspects of the presales lifecycle-from business and technical discovery, solution architecture, estimation, and proposal development to Proof of Concept (POC) and delivery handover.

The ideal candidate has hands-on experience delivering Databricks and large-scale data engineering projects, a strong understanding of modern cloud data architectures, and proven experience working with global enterprise clients and distributed teams.

Key Responsibilities

I. Customer Discovery & Solution Design

• Lead technical and business discovery sessions with enterprise clients to understand their business objectives, existing data landscape, technical challenges, and transformation priorities.
• Translate business requirements into scalable big data, data engineering, analytics, and cloud data platform solutions.
• Design end-to-end solution architectures covering areas such as:
• Data ingestion and integration
• Data lake and lakehouse architecture
• Batch and real-time data processing
• Data transformation and orchestration
• Data modeling and analytics
• Data governance, security, and access control
• Cloud data platform modernization and migration
• Design solutions leveraging Databricks and related cloud data services across AWS, Azure, or GCP.
• Assess clients' existing data platforms and recommend practical modernization and migration approaches based on business value, technical feasibility, scalability, and cost.

II. Technical Presales & Solution Demonstration

• Develop and present tailored solution proposals, architecture designs, and technical demonstrations based on specific client requirements and industry scenarios.
• Communicate both high-level business value and detailed technical solutions to different audiences, including C-level executives, business stakeholders, architects, and engineering teams.
• Lead technical responses for RFIs, RFPs, and RFQs, ensuring proposed solutions are technically sound, commercially competitive, and aligned with client requirements.
• Lead or support Proof of Concept (POC) and technical validation activities to demonstrate solution feasibility and business value.
• Conduct technical workshops, architecture discussions, and solution review sessions with global clients.
• Support effort estimation, technical scope definition, assumptions, dependencies, and delivery planning during the presales process.

III. Presales Project Management

• End-to-End Presales Management: Own the technical presales lifecycle from requirements discovery and solution architecture through proposal submission and delivery handover.
• Multi-Opportunity Management: Manage multiple client opportunities at different stages and prioritize activities based on deal value, strategic importance, complexity, and deadlines.
• Cross-Functional Coordination: Collaborate closely with Sales, Delivery, Engineering, Cloud, Data, and Project Management teams to develop feasible and competitive solutions.
• Bid & Proposal Management: Lead technical activities throughout the bid process, including requirements analysis, solution architecture, estimation, compliance review, risk identification, and final submission.
• Handover Management: Ensure a smooth transition from presales to implementation teams, with clear documentation of scope, architecture, assumptions, dependencies, risks, and client expectations.

IV. Global Client Engagement & Technology Leadership

• Work directly with global enterprise clients, collaborating across different regions, cultures, and time zones.
• Build trusted technical relationships with client architects, engineering leaders, data teams, and senior stakeholders.
• Work effectively with distributed and cross-functional teams across different countries and regions.
• Partner with internal Engineering, Delivery, Product, and Business teams to identify reusable solution patterns, accelerators, and best practices.
• Provide technical enablement and knowledge sharing to sales, presales, and delivery teams.
• Stay current with developments in Databricks, cloud data platforms, lakehouse architecture, data engineering, analytics, and AI/ML technologies.
• Contribute to the development of reusable reference architectures, solution frameworks, technical assets, and industry-specific offerings.

Required Qualifications

Education: Bachelor's degree or above in Computer Science, Engineering, Information Technology, or a related field.

Professional Experience

• 6+ years of experience in data engineering, solution architecture, technical consulting, or presales roles, with significant experience designing complex enterprise data solutions.
• Proven experience working in a technical presales, solution architecture, or client-facing consulting role.
• Hands-on project experience with Databricks, preferably involving production-scale implementations rather than only training, certification, or POC environments.
• Experience designing or delivering large-scale data engineering, data lake, lakehouse, or cloud data platform solutions.
• Proven experience working directly with global enterprise clients, including technical workshops, solution discussions, presentations, and stakeholder management.
• Experience collaborating with distributed delivery and engineering teams across multiple regions.

Technical Skills

• Strong understanding of modern big data and data engineering architectures.
• Strong hands-on knowledge of Databricks, including key concepts such as:
• Delta Lake
• Lakehouse architecture
• Spark-based data processing
• Data pipelines and orchestration
• Databricks SQL
• Unity Catalog and data governance
• Strong understanding of data ingestion, ETL/ELT, batch and streaming processing, data modeling, and data integration patterns.
• Experience with at least one major cloud platform: AWS, Microsoft Azure, or Google Cloud Platform.
• Familiarity with cloud-native data services, data warehouses, object storage, messaging, orchestration, and analytics technologies.
• Understanding of enterprise data governance, security, access control, data quality, and compliance principles.
• Familiarity with APIs, integration patterns, and modern data ecosystem components.
• Ability to design scalable, secure, reliable, and cost-effective enterprise data architectures.

Presales & Project Management Skills

• Proven experience managing technical activities throughout the presales lifecycle, from discovery and solution design to proposal and delivery handover.
• Strong experience with RFP/RFI/RFQ responses, bid management, solution estimation, and technical proposal development.
• Experience leading technical workshops, architecture reviews, and POCs.
• Ability to manage multiple opportunities and priorities simultaneously.
• Strong ability to identify solution risks, assumptions, dependencies, and technical trade-offs.

Communication & Influence

• Excellent verbal and written English communication skills, with the ability to work effectively with international clients and teams.
• Strong presentation and storytelling skills, with the ability to connect technical solutions to business outcomes.
• Confident engaging with stakeholders at different levels, from engineers and architects to senior management and C-level executives.
• Ability to simplify complex technical concepts for non-technical audiences.
• Strong stakeholder management, collaboration, and influencing skills.

Preferred Qualifications

• Experience with Databricks Data Intelligence Platform in large-scale enterprise environments.
• Databricks certifications such as Databricks Certified Data Engineer, Data Engineer Professional, or related certifications.
• Experience with multiple cloud platforms, particularly AWS and Azure.
• Experience with technologies such as Apache Spark, Kafka, Airflow, dbt, Snowflake, Microsoft Fabric, or similar modern data platforms.
• Experience in enterprise data platform modernization or migration programs.
• Understanding of AI/ML, Generative AI, and their integration with enterprise data platforms.
• Familiarity with data privacy and compliance frameworks such as GDPR and CCPA.
• Experience working in consulting, system integration, or global technology service organizations.
• Relevant cloud certifications from AWS, Microsoft Azure, Google Cloud, or Databricks.