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VALENTA
Director

Director of Data & AI Engineering

VALENTAVisit website ·Posted 1 month ago

Location

KA, IN

Experience

5+ years

Required Skills

PythonAzureSQLAISAPTableauPower BI

About the Role

Job Information Industry


IT Services
Current Openings


1
Job Type


Full time
Work Experience


  • years

  • Salary


    As per company standards
    Date Opened


    05/04/2026
    Hiring Manager


    Vaishali Agrawal
    City


    Bangalore
    State/Province


    Karnataka
    Country


    India
    Zip/Postal Code


    560112

    Job Description

    We are seeking a highly experienced and technically strong leader to head our Data . AI Engineering function. This role will be responsible for driving the technical vision, delivery excellence, and AI-first transformation across our data engineering and analytics teams.
    The ideal candidate will bring a
    hands-on leadership approach, combining deep expertise in data platforms and applied AI with the ability to guide teams, architect scalable solutions, and deliver measurable business outcomes.
    Role Summary: -----------------

    This position requires a strategic yet hands-on leader who can operate across data engineering, analytics, and AI, and drive the organization toward becoming a truly AI-native delivery function. The role demands a balance of **technical depth, leadership capability, and business acumen to deliver impactful, scalable, and future-ready solutions.
    Key Responsibilities:**


  • • Define and implement the AI-first engineering strategy, including standards, frameworks, and best practices across all engagements

  • • Lead, mentor, and scale a cross-functional team of data engineers, analysts, and integration specialists

  • • Drive adoption of AI-assisted development tools (e.g., Cursor, Claude Code, GitHub Copilot) as an integral part of the engineering workflow

  • • Design and deliver advanced AI solutions, including:


  • + LLM integrations ( Large Language Model)
    + Prompt engineering frameworks
    + Agentic workflows
    + RAG-based architectures

  • • Architect and oversee end-to-end data solutions, including cloud data platforms, ERP integrations, and reporting systems

  • • Act as the technical authority, providing hands-on guidance through solution design, code reviews, and engineering best practices

  • • Collaborate with internal stakeholders and clients to identify opportunities for AI-driven optimization and automation

  • Establish and enforce *data governance, quality standards, and responsible AI practices.
    Required Experience**

  • • 10. years of experience in data engineering, analytics, or data platform development

  • • Minimum 5 years of hands-on experience in applied AI/ML, including LLMs and modern AI frameworks

  • • Proven, day-to-day experience with AI-assisted development tools (such as Cursor, Claude Code, GitHub Copilot)

  • • Demonstrated success in leading technical teams within consulting or managed services environments

  • • Strong ability to translate technical solutions into business value for stakeholders. Mandatory Key Skills ------------------------

  • Core Technical Skills

  • • Strong proficiency in Python and SQL (including stored procedures)

  • • Hands-on experience with cloud data platforms (Azure, Snowflake, Databricks)

  • • Expertise in building and managing ETL/ELT pipelines

  • Experience with *business intelligence tools (Power BI, Tableau, Looker)

    AI . Advanced Capabilities**

  • • Deep understanding of:


  • + Large Language Models (LLMs) + Prompt engineering techniques + RAG (Retrieval-Augmented Generation) architectures + Agentic AI frameworks

  • • Experience designing and deploying production-grade AI solutions

  • Regular usage of *AI-assisted development tools in coding and delivery workflows

    Leadership . Stakeholder Skills**

  • • Proven experience in team leadership, mentoring, and capability building

  • • Strong architecture and code review expertise

  • Ability to communicate effectively with both *technical and non-technical stakeholders

    Business . Consulting Orientation**

  • • Strong problem-solving skills with the ability to convert business requirements into scalable technical solutions

  • • Experience in client-facing roles and consulting environments

  • Ability to articulate *business impact and ROI of data and AI initiatives
    Preferred Qualifications (Good to Have)**

  • • Experience with ERP platforms (SAP, Dynamics, Plex)

  • • Familiarity with workflow automation tools (e.g., n8n)

  • • Background in leading analytics consulting firms (e.g., Tiger Analytics, Fractal, Tredence)

  • • Contributions to open-source AI or data engineering projects.
  • below are the Mandatory skill sets

  • • Strong programming expertise in Python and SQL (including stored procedures)

  • • Hands-on experience in building and managing ETL/ELT data pipelines

  • • Experience with cloud data platforms (Azure, Snowflake, Databricks)

  • • Solid understanding of data architecture and end-to-end data engineering workflows

  • • Proven hands-on experience with Applied AI, including:


  • + Large Language Models (LLMs)
    + Prompt Engineering
    + RAG (Retrieval-Augmented Generation) architectures
    + Agentic AI / workflow frameworks

  • • Demonstrated experience in building and deploying AI solutions in production environments

  • • Regular, hands-on usage of AI-assisted development tools such as:


  • + Cursor
    + Claude Code
    + GitHub Copilot

  • • Experience in technical leadership, including:


  • + Leading/mentoring engineering teams
    + Solution architecture and design
    + Code reviews and technical governance

  • • Strong understanding of data . analytics ecosystem, including BI tools (Power BI, Tableau, or Looker)

  • • Experience working in client-facing or consulting environments

  • • Ability to translate business requirements into scalable technical solutions

  • Strong *communication and stakeholder management skills, including explaining technical concepts to non-technical audiences

    HireIQ AI InsightsBeta

    Ideal Candidate

    Someone who has scaled data engineering teams at consulting firms (Deloitte, Accenture, TCS) while shipping production LLM solutions—not just experimenting with them.

    Estimated Salary Range(medium confidence)

    22 L – ₹35 L per year

    Likely Interview Questions

    1. 1.Walk us through a production LLM or RAG system you architected end-to-end—what was the business problem, which framework did you choose and why, and what governance/quality controls did you implement?
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    🔒 Strengths to highlight + red flags locked.

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