The role
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
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- 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.