Presales Solution Architect- Data Analytics

9 hours ago


Navi Mumbai, Maharashtra, India 3i Infotech Full time ₹ 12,00,000 - ₹ 36,00,000 per year

Solution Architect Data Analytics (Presales)

Position Overview

We are looking for a Solution Architect cum Presales Leader with deep expertise in Data Engineering, Analytics, and AI/ML solutions. This role requires a unique blend of technical architecture, presales solutioning, and client engagement skills to help win new business opportunities, design scalable solutions, and enable delivery excellence across global clients.

Key Responsibilities

Presales & Client Engagement

  • Partner with sales and business teams to identify opportunities in Data Engineering, Analytics, BI, and AI/ML.
  • Conduct discovery workshops with clients to understand pain points, data landscape, and business objectives.
  • Prepare winning RFP/RFI responses, solution decks, cost models, and PoCs.
  • Deliver demos, technical presentations, and thought leadership sessions to CXO and senior stakeholders.
  • Define value propositions, ROI models, and differentiators for data/analytics opportunities.

Solution Architecture & Design

  • Design end-to-end Data & Analytics architectures including:

  • Data Engineering: ingestion, pipelines, ETL/ELT, data lakes, warehouses, lakehouses.

  • Analytics: BI dashboards, reporting, self-service analytics, advanced analytics.
  • AI/ML Integration: predictive, prescriptive, NLP, GenAI, and data-driven automation.

  • Define reference architectures leveraging modern platforms (Snowflake, Databricks, BigQuery, Synapse, Redshift, etc.).

  • Architect scalable solutions on AWS, Azure, or GCP cloud ecosystems.
  • Ensure security, compliance, and data governance are embedded in solutions.
  • Build reusable assets, accelerators, and frameworks for faster presales cycles.

Delivery Enablement & Governance

  • Collaborate with delivery leads to ensure solution feasibility and alignment.
  • Provide technical governance during transition/mobilization phases.
  • Define SLAs, KPIs, and governance frameworks for data & analytics programs.
  • Support estimation of efforts, resources, and delivery planning.

Innovation & Thought Leadership

  • Drive innovation in AI/ML, GenAI for data, and modern data architectures (lakehouse, data mesh).
  • Mentor solution consultants and delivery architects on presales and solutioning best practices.
  • Represent the organization in conferences, client forums, and leadership workshops.

Key Performance Indicators (KPIs)

  • Win ratio on data/analytics opportunities supported.
  • Revenue growth influenced by data/analytics deals.
  • Solution accuracy vs. delivery execution (variance 10%).
  • Number of PoCs, accelerators, and reusable assets created.
  • Customer CSAT/NPS for delivered data programs.

Required Skills & Qualifications

Technical Skills

  • Strong expertise in Data Engineering: ETL/ELT, data lakes, warehouses, real-time streaming (Kafka, Kinesis, Spark, Flink).
  • Proficiency in Analytics & BI tools: Power BI, Tableau, Qlik, Looker.
  • Knowledge of Data Science/AI frameworks: Python (pandas, scikit-learn), TensorFlow, PyTorch, NLP/LLMs.
  • Experience with Cloud Platforms: AWS (Redshift, Glue, Athena), Azure (Synapse, Data Factory), GCP (BigQuery, Dataflow).
  • Familiarity with Data Governance, MDM, and Data Security frameworks.
  • Understanding of modern architectures: data mesh, data fabric, lakehouse.

Presales Skills

  • Experience in preparing RFP/RFI responses, estimation models, and solutioning.
  • Excellent client communication, proposal writing, and presentation skills.
  • Ability to articulate ROI and business value in client conversations.

General Skills

  • 5-10 years of IT experience, with at least 5+ years in solution architecture & presales.
  • Strong leadership, analytical, and stakeholder management skills.
  • Track record of winning Data/Analytics deals and enabling delivery success.
  • Willingness to travel for client workshops and presales engagements.

Education & Certifications

  • Bachelors/Masters in Computer Science, Engineering, or related field.
  • Preferred Certifications:

  • Cloud: AWS Data Analytics Specialty, Azure Data Engineer, GCP Professional Data Engineer.

  • BI: Microsoft Power BI, Tableau Specialist.
  • Architecture: TOGAF, Data Management certifications (DAMA/CDMP).


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