About the Role

The Data Engineering & AI Practice Lead owns the end-to-end health of the Data Engineering and AI practice within our IT services business. This is a hybrid leadership role that combines technical depth with client-facing gravitas - you will shape the practice's offerings, win current business in presales, architect solutions during solutioning, and drive delivery excellence across active engagements. You will act as the "go-to" authority for all things data and AI inside the firm, bridging the gap between what clients need and what our engineering teams deliver.

Key Responsibilities

1. Presales & Business Development

Collaborate with Sales and Account Management teams to qualify and pursue data & AI opportunities.

Lead client discovery workshops to uncover pain points, assess data maturity, and identify high-value AI use cases.

Author and present compelling proposals, RFP responses, and capability decks tailored to each prospect's business context.

Define competitive pricing models, effort estimates, and engagement constructs (T&M;, fixed-price, outcome-based).

Build and maintain a reusable presales asset library: solution blueprints, case studies, demo environments, and ROI calculators.

Represent the practice at industry conferences, webinars, and client briefings to establish thought leadership.

2. Solutioning & Architecture

Lead architecture design for data platform, AI/ML, and analytics engagements - from conceptual to detailed solution design.

Define reference architectures across modern data stack components: ingestion, lakehouse/ warehouse, orchestration, serving, and AI/ML pipelines.

Evaluate and recommend technology choices (e.g., Databricks, Snowflake, dbt, Apache Spark, Azure/AWS/GCP native services, LLM frameworks).

Produce high-quality SOWs, architecture decision records (ADRs), and solution design documents.

Drive POC/prototype builds to validate technical feasibility and de-risk client commitments.

Stay current on emerging trends (GenAI, LLMOps, real-time streaming, data mesh,



data contracts) and translate them into practice offerings.

3. Delivery Excellence

Establish and govern delivery standards, engineering best practices, and quality gates across active data & AI projects.

Define and enforce CI/CD, testing, data quality, observability, and documentation standards for the practice.

Conduct milestone reviews and architecture governance checkpoints to identify risks early.

Serve as executive escalation point for critical delivery issues; provide hands-on guidance to project teams.

Build and own the practice's capability roadmap: identify skill gaps, drive training, and recruit senior talent.

Track practice-level KPIs (utilization, CSAT, delivery quality, reuse index) and report to leadership.

4. Practice Building & Thought Leadership

Define and maintain the practice's service catalog, go-to-market positioning, and tiered offering structure.

Create and evangelize accelerators, frameworks, and IP assets that reduce time-to-value for clients.

Mentor architects and senior engineers; run internal CoPs (Communities of Practice) for data engineering and AI.

Partner with technology alliance teams (Databricks, Snowflake, AWS, Azure, Google) to deepen partnerships and co-sell.

Qualifications

Required

15+ years of hands-on experience in data engineering, analytics, or AI/ML with at least 3 years in a practice lead, principal architect, or senior manager capacity at an IT services or consulting firm.

Deep expertise in modern data platforms: lakehouses (Databricks, Apache Iceberg), cloud data warehouses (Snowflake, BigQuery, Redshift), and orchestration (Airflow, dbt, Prefect).





Proven track record of winning and delivering data/AI engagements worth $500K $5M+.

Strong cloud fluency across at least two hyperscalers (AWS, Azure, or GCP) including their native data and AI services.

Experience architecting and delivering ML/AI solutions including feature engineering, model training, deployment, and monitoring pipelines.

Excellent written and verbal communication; able to present technical concepts to C-suite and business stakeholders.

Experience with GenAI/LLM-based solutions: RAG architectures, fine-tuning, prompt engineering, and LLMOps.

Communication and presentation skills must be excellent.

Excellent stakeholder management skills.

VDart: Digital Consulting & Staffing Solutions

VDart is a leading digital consulting and staffing company founded in 2007 and headquartered in Alpharetta, Georgia. VDart is one of the top staffing companies in USA & also provides technology solutions, supporting businesses in their digital transformation journey. Digital consulting services, Digital consulting agency

Core Services:

- Digital consulting and transformation solutions
- Comprehensive staffing services (contract, temporary, permanent placements)
- Talent management and workforce solutions
- Technology implementation services

Key Industries: VDart primarily serves industries such as automotive and mobility, banking and finance, healthcare and life sciences, and energy and utilities. VDart - Products, Competitors, Financials, Employees, Headquarters Locations

Notable Partnership: VDart Digital has been a consistently strong supplier for Toyota since 2017 Digital Transformation Consulting & Strategy Services | VDart Digital, demonstrating their capability in large-scale digital transformation projects.

With over 17 years of experience, VDart combines staffing expertise with technology solutions to help organizations modernize their operations and build skilled workforce capabilities across multiple sectors.

📌 Data Practice Lead (Bengaluru)
🏢 VDart Software Services
📍 Bengaluru