Data Analytics Pre-Sales and Delivery Manager

Cloud Kinetics Technology Solutions Private Ltd | Full time

Data Analytics Pre-Sales and Delivery Manager

San Francisco, United States | Posted on 10/07/2024

Responsibilities

1. As a Data & Analytics pre-sales engineer/architect, partner with sales account manager/sales rep and lead the technical win.
2. As a delivery manager, participate, lead or aid timely and high-quality service delivery of Data & Analytics projects and engagements.
3. Unearth, identify and flesh out customer's technical needs and current landscape of data, analytics and related applications.
4. Identify key customer technology priorities and timelines related to Data & Analytics (Data modernization/migration to cloud, BI and self-service analytics, AI/ML and/or GenAI).
5. Position CK as a specialist with relevant expertise and credentials to address customer's specific needs, leveraging CK's sales and technical collateral and tailoring it to address customer needs.
6. Own or orchestrate the creation of the technical sections of successful service proposals, collaborating internally with subject matter experts as needed.
7. Vet proposed delivery approach, methodology and timelines to ensure that they match customer's needs.
8. Collaborate effectively with internal teams by clearly defining or clarifying scope and lead or aid POCs.
9. Where feasible, take on a hands-on delivery approach (e.g. POCs) in collaboration with remote delivery teams.
10. For medium to large accounts and engagements, function as an effective near-shore point of contact between customer and remote delivery teams.
11. Map out customers' technology and data/app landscape, key technology decision makers/influencers.
12. Identify other potential opportunities to engage and deepen/expand CK's relationship with customer.
13. Attend delivery standup meetings and customer interactions.
14. Understand and communicate status of various projects and milestone attainment with relevant customer stakeholders.
15. Gather customer inputs that would help advance project execution.
16. Identify and resolve key dependencies/roadblocks.
17. Initially, the pre-sales responsibilities will likely take up more of the time. Over time, the mix of pre-sales to technical account management might shift to 60:40.

Requirements

1. Relevant background/experience
2. Good cloud technology background with deep hands-on solutioning and implementation experience in architecting and implementing end-to-end Data & Analytics solutions.
3. Interest and familiarity in developing and deploying GenAI applications targeting mid-market and enterprise customers.
4. Good understanding and prior experience in developing software using the Agile software development methodology.
5. Great communication and presentation skills with exec-level presence and the ability to gain credibility with senior (Director and higher) technology decision makers/influencers.
6. Solid first-principles approach to problem solving – ability to break down a problem, structure solutions and communicate recommendations with justifications.
7. Prior experience in pre-sales and interest in technical account management/delivery roles.
8. Relevant experience with AWS and associated ecosystem would be preferred; Azure experience would be a plus.
9. Collaborative and team-oriented nature, with ability to work effectively with sales and other internal teams (e.g. delivery, finance etc.).
10. Entrepreneurial and can-do attitude.
11. Data engineering using AWS and open-source ETL/ELT technology and tools; good knowledge and experience with SQL and Python or Scala.
12. Architecting and implementing cloud and hybrid cloud data repositories including data warehouses, data lakes and data lake houses; knowledge of AWS-native platforms with working experience in Snowflake or Databricks.
13. Experience implementing self-service analytics solutions and data migration/modernization from legacy data sources; data modeling experience would be a plus.
14. Understanding of foundational models and technology frameworks.
15. Working knowledge of prompt engineering, RAG, model fine-tuning etc.; prototyping or development experience with GenAI applications would be a plus.
16. Understanding customer's technology needs and link them to key business priorities.
17. Experience delivering technical wins in single vendor and competitive (RFP) scenarios.
18. Understanding and learnings from creating successful services proposals - clear idea of what good, great proposals look like.