
Solution Architect-Data
1 day ago
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 ResponsibilitiesA) 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.
- 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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