Product Evangelist

Requirements

developer advocacy

Solution Architecture

educate and empower developer communities

advising enterprise customers

Big Data platforms (Databricks, Snowflake, Hadoop, Kafka, MongoDB, etc.)

LLMs, AI/ML, and distributed systems

community-facing developer advocacy

strategic solution architecture consulting

Key Responsibilities:

Developer Advocacy & Community Building

• Create authentic technical resources: open source demos, code samples, documentation, how-to guides, tutorials, and blogs
• Build awareness and motivate developers to build applications, data pipelines, and data science workflows on our platform
• Engage in communities like Stack Overflow, GitHub, Slack, Reddit, Discord to support developers and identify new resources
• Deliver impactful talks at conferences, meetups, and events, showcasing solutions, best practices, and platform capabilities
• Collaborate with product teams to communicate developer needs and influence roadmap
• Define and own success metrics for developer engagement, content reach, and community growth
  

Solution Architecture & Customer Success

:

• Partner with enterprise customers as a trusted technical advisor, guiding their Data & AI transformation initiatives
• Architect and implement scalable solutions across data engineering, data science, analytics, and ML/AI workflows
• Lead customer workshops, proof-of-concepts, migrations, and complex delivery programs
• Consult on cloud-native architectures, integrations, and data governance/security (Unity Catalog, RBAC)
• Advise customers on competitive landscapes (Snowflake, Databricks, EMR, Sagemaker, MongoDB Atlas, etc.)
• Collaborate with cross-functional teams: product engineering, marketing, customer success, and partner organizations
• Mentor internal teams and customers on best practices, distributed computing, and modern data architectures
  

Required Skills:

Must-Have:

• 7-10+ years of experience in Developer Relations, Developer Advocacy, or Solution Architecture
• Proven expertise in Big Data technologies (Apache Spark, Kafka, Data Lakes, Hadoop, Cassandra, Delta Lake, Trino)
• Strong coding experience in at least two of: Python, PySpark, Java, Scala, JavaScript, Go, Ruby, R, or C#
• Hands-on experience with LLMs and AI/ML platforms (Langchain, LlamaIndex, HuggingFace, mistral, Pinecone, Weaviate, MLflow)
• Proficiency with data platforms and cloud ecosystems: Databricks Lakehouse, Snowflake, MongoDB, Postgres, NoSQL (MongoDB, Redis, HBase), and at least one of AWS, Azure, or GCP
• Strong background in SQL, Spark SQL, Spark Streaming, distributed computing, and cloud-native architectures
• Knowledge of MLOps, GenAI solutions, and scalable production deployments is a plus
• Exceptional communication, technical writing, whiteboarding, and presentation skills
• Experience working with cross-functional teams and in customer-facing roles
• Willingness to travel (:30%) for conferences, events, and onsite customer engagements
  

Good-to-Have:

• Experience delivering LLM/GenAI solutions at scale (RAG, prompt engineering)
• Contributions to open source projects or active presence in developer communities
• Databricks or Snowflake certifications
• Experience founding, pitching, or advising startups
• Strong storytelling ability in both written and spoken mediums (blogs, talks, videos, webinars)
  

Eligibility / Qualifications:

• Education: Any Undergraduate (or) Postgraduate
• Experience: 7- 20 Years