Solution Architect-Data

1 week ago

Bengaluru, India i4 Consulting: Reimagining HR Blueprints Full time

Were looking for an experienced Solution Architect to lead solutioning and presales activities in the Modern Data & AI Platforms space. This role involves driving proposals, customer engagements, technical leadership, and innovation for complex data engineering projects.


Key Responsibilities

A) Solutioning & Presales (80%)

  • Architect and solution modern data & AI platforms.
  • Lead presales, proposals, and solution development across verticals.
  • Respond to RFPs, lead proposal defenses, and anchor technical solutioning.
  • Drive solution roadmaps based on market and technology trends.
  • Conduct client discovery sessions and design technical blueprints.
  • Build solution offerings, use cases, POVs, and technical content.
  • Develop the partner ecosystem and represent the practice in industry forums.
  • Mentor and upskill project teams in core tech areas.

B) Client Jumpstart & Innovation Projects (20%)

  • Blueprint and plan complex data engineering programs.
  • Drive pilots, PoCs, and innovation-led engagements.
  • Manage scope, effort estimates, commercials, and stakeholder relationships.
  • Validate technical outcomes and recommend improvements.

Required Skills & Experience
  • 14+ years of experience, with at least 5 years in solutioning and presales.
  • Proven experience in modern data architectures on AWS or GCP : data mesh, fabric, unified platforms, operational/AI data systems.
  • Hands-on presales exposure in product engineering service lines or startups .
  • Domain exposure: Manufacturing, Hi-Tech, ISVs, Automotive, ENU, Communications, BFSI.
  • Expertise in unstructured data processing, vectorization, chatbot integration, and graph technologies.
  • Strong knowledge of solution architecture, data modeling, and ontology.
  • Hands-on with data governance (catalogs, lineage, quality).
  • Proven experience across hybrid landscapes integrating OT, ET, unstructured, and time-series data.
  • Familiarity with tools and technologies across:
  • Graph DBs : AWS Neptune, Neo4j, Apache Gremlin, JanusGraph, ArangoDB
  • Vector DBs : Pinecone, Milvus, Chroma, Google AlloyDB
  • Big Data : AWS Redshift, GCP BigQuery, Databricks, Delta Lake, NoSQL (DynamoDB, Cassandra, HBase)
  • Pipelines : AWS EMR, Glue, Kinesis, Step Functions, GCP Dataflow, Pub/Sub, Spark
  • Governance Tools : AWS Glue Crawler, Google Data Catalog, Apache Atlas, OpenLineage


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