Job Title:  T&T : Senior Consultant - Engineering, AI & Data

ONLY LOCAL CANDIDATES ARE ELIGIBLE TO APPLY

Job Overview

We are seeking a Senior Consultant with strong cross‑domain experience across data engineering, analytics, visualization, and AI, with a firm grasp of data modelling, structured problem solving, and solution design.

This role is design‑ and oversight‑focused, responsible for shaping analytical and AI solutions, guiding delivery teams, and ensuring alignment between business requirements and technical outcomes. The successful candidate will work closely with stakeholders to translate complex problems into well‑architected, scalable, and governed solutions, including emerging Generative AI and Agentic AI use cases.

Key Responsibilities

Problem Solving, Solution Design & Architecture

• Lead problem definition and solution design for data, analytics, AI, and visualization initiatives.
• Translate business requirements into clear analytical and technical solution designs, including architecture, data models, and delivery approaches.
• Design and review conceptual, logical, and physical data models, ensuring alignment with business use cases and long‑term scalability.
• Define end‑to‑end solution architectures covering data ingestion, transformation, modelling, analytics, AI/ML, GenAI, and visualization layers.
• Ensure solutions follow sound architectural principles, balancing performance, maintainability, and extensibility.

Generative AI & Agentic AI

• Contribute to the design and shaping of Generative AI and Agentic AI solutions, such as copilots, intelligent assistants, and automated analytical workflows.
• Ensure GenAI solutions are grounded in strong data foundations, with appropriate governance, controls, and explainability.
• Support the identification of practical, business‑relevant GenAI use cases, avoiding purely experimental implementations.

Presales & Solution Shaping

• Support presales activities, including solution ideation, technical inputs to proposals, and effort estimation.
• Participate in client discussions and workshops to clarify requirements, explore solution options, and explain design trade‑offs.
• Assist in shaping solution narratives and value propositions for data, analytics, and AI initiatives.

Analytics & Visualization Enablement

• Oversee the design of analytical and visualization layers that support decision‑making.
• Ensure dashboards and analytical outputs are intuitive, insight‑driven, and aligned to business questions, not just technically correct.
• Review semantic models and analytical logic to ensure consistency and reusability.

Data Governance & Quality

• Incorporate data governance, data quality, lineage, and access controls into solution designs.
• Ensure solutions align with enterprise governance and regulatory expectations, particularly relevant to Sri Lankan organisations.

Team Guidance & Delivery Oversight

• Provide technical guidance and oversight to delivery teams across data engineering, analytics, AI, and visualization.
• Review designs and outputs to ensure quality, consistency, and adherence to standards.
• Mentor junior team members and contribute to capability development through knowledge sharing and coaching.

Requirements

Core Skills

• Data Modelling: Strong experience with dimensional and analytical data models (conceptual, logical, physical).
• Solution Design & Architecture: Proven ability to design end‑to‑end data and analytics solutions.
• Data Engineering Concepts: Solid understanding of modern data pipelines and platforms (hands‑on experience beneficial but not mandatory).
• Data Governance: Understanding of data quality, metadata, lineage, security, and access management.
• Generative AI & Agentic AI: Experience contributing to or supporting the design of GenAI‑enabled solutions.

Analytical & Professional Skills

• Strong structured thinking and problem‑solving ability.
• Ability to translate business problems into analytical and technical designs.
• Strong communication skills, with the ability to explain complex concepts to non‑technical stakeholders.
• Experience working in multi‑stakeholder, delivery‑oriented environments.