Databricks Pre-Sales and Solutions Architect

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Role : Databricks Pre-Sales and Solutions Architect

Location : PAN India

Mode : Full Time

Experience : 10-16 years

1. Pre-Sales Support and Technical Leadership :

a. Engage with customers early in the sales process to understand their technical and business requirements

b. Deliver tailored product demonstrations and presentations that highlight Databricks' capabilities, architecture, and unique differentiators.

c. Collaborate with sales teams to identify and address customer pain points, aligning Databricks solutions to customer needs

d. Lead customer discussions, workshops, and meetings to understand their business challenges and translate them into actionable technical solutions

e. Present and articulate Databricks value propositions and architecture at various organizational levels

2. Solution Design and Architecture :

a. Design scalable and secure architectures using Databricks, ensuring alignment with customer requirements and best practices

b. Create and present high-level and detailed technical solutions, including deployment architecture, data pipeline designs, and integration strategies with other tools

c. Provide guidance on cloud architecture, big data technologies, machine learning, and AI use cases.

d. Collaborate with customers to design POCs and proof-of-concept solutions to showcase the capabilities of Databricks

3. Collaboration with Sales and Technical Teams :

a. Partner with the sales team to define and drive the sales strategy, assisting in closing high-value deals

b. Collaborate with the Databricks engineering, product, and support teams to ensure smooth solution delivery and customer success

c. Assist in the creation of sales collateral, technical documentation, white papers, and case studies.

4. Customer Relationship and Post-Sales Support :

a. Maintain strong relationships with key stakeholders throughout the customer lifecycle

b. Act as a trusted advisor for technical solutions and best practices for Databricks customers

c. Help customers with troubleshooting, performance optimization, and ensuring successful implementation and adoption of Databricks

5. Market Intelligence and Training :

a. Stay current with industry trends, new technologies, and Databricks product updates

b. Share feedback from customers and prospects with the product management and engineering teams to help influence future product roadmaps.

c. Train and mentor junior solution architects or pre-sales engineers.

Skills and Qualifications :

1. Educational Background :

Bachelor's degree in Computer Science, Engineering, Information Technology, or a related field (Master's preferred).

2. Certifications :

a. Databricks Certified Professional Data Engineer

b. AWS Certified Solutions Architect or similar certification

c. Google Cloud Professional Data Engineer or Azure Data Engineer certifications are a plus.

3. Technical Expertise :

a. Deep understanding of Databricks' platform, Apache Spark, and data engineering principles

b. Experience with cloud platforms (AWS, Azure, GCP) and their integration with Databricks.

c. Knowledge of big data technologies such as Hadoop, Kafka, and other data processing frameworks.

d. Proficiency in Python, Scala, SQL, or similar languages commonly used in data engineering and machine learning.

e. Experience with machine learning and data science tools, including but not limited to TensorFlow, PyTorch, Scikit-learn, and MLflow

4. Architecture and Design

a. Strong understanding of data architecture, data pipelines, and ETL processes

b. Experience designing and deploying scalable, secure, and high-performance solutions.

c. Experience with containerization, microservices, and DevOps practices.

5. Experience :

a. 5+ years of experience in technical presale, solution architect, or similar customer-facing role.

b. Previous experience with Databricks or Spark-based technologies is a plus.

Experience with machine learning frameworks and pipelines, particularly in Databricks.

c. Experience with AI / ML model deployment, MLOps, and ML lifecycle management using Databricks and related tools.

d. Cloud certifications (AWS, Azure, or GCP).

e. Experience in industries such as finance, healthcare, e-commerce, or manufacturing is a plus.

Skills Required

Hadoop, Scala, Apache Spark, Data Architecture, Kafka, Sql, Microservices, Tensorflow, Devops, Pytorch, Gcp, containerization , Databricks, Azure, Python, Aws