Associate Director - Presales Architect (Data & Analytics)

2 - 6 years

0 Lacs

Posted:1 week ago| Platform: Shine logo

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Job Type

Full Time

Job Description

As a data architecture leader, you will play a crucial role in driving data warehousing and data center architecture initiatives. Your expertise in Data Warehousing, Data Lakes, Data Integration, and Data Governance, combined with hands-on experience in ETL tools and cloud platforms such as AWS, Azure, GCP, and Snowflake, will be highly valuable. Your responsibilities will encompass technical leadership, presales support, and managing complex enterprise deals across different regions. **Key Responsibilities:** - Architect and design scalable Data Warehousing and Data Lake solutions - Lead presales engagements and manage the RFP/RFI/RFQ lifecycle - Develop and present compelling proposals and solution designs to clients - Collaborate with cross-functional teams to deliver end-to-end solutions - Estimate efforts and resources for customer requirements - Drive Managed Services opportunities and enterprise deal closures - Engage with clients in MEA, APAC, US, and UK regions - Ensure solutions align with business goals and technical requirements - Maintain high standards of documentation and presentation for client-facing materials **Qualification Required:** - Bachelor's or Master's degree in Computer Science, Information Technology, or related field - Certifications in AWS, Azure, GCP, or Snowflake are advantageous - Experience in consulting or system integrator environments - Proficiency in Data Warehousing, Data Lakes, Data Integration, and Data Governance - Hands-on experience with ETL tools (e.g., Informatica, Talend, etc.) - Exposure to cloud environments: AWS, Azure, GCP, Snowflake - Minimum 2 years of presales experience with an understanding of presales operating processes - Experience in enterprise-level deals and Managed Services - Ability to handle multi-geo engagements effectively - Excellent presentation and communication skills - Strong understanding of effort estimation techniques for customer requirements,

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